Triple
T14940591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ngawi Regency |
E372513
|
entity |
| Predicate | hasVehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
AE
AE is an Indonesian vehicle registration code assigned to motor vehicles registered in Ngawi Regency and certain surrounding areas in East Java.
|
E1129084
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: AE | Statement: [Ngawi Regency, hasVehicleRegistrationCode, AE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AE Context triple: [Ngawi Regency, hasVehicleRegistrationCode, AE]
-
A.
AE
AE is the commonly used abbreviation for Academia Europaea, a European non-governmental association of scientists and scholars across all disciplines.
-
B.
AE
AE is the IATA airline designator assigned to Mandarin Airlines, a regional carrier based in Taiwan.
-
C.
AE
AE is the standard abbreviation for a DICOM Application Entity, which represents a logical device or software component that exchanges medical imaging data within a DICOM network.
-
D.
AE
AE is the Faculty of Aerospace Engineering at Delft University of Technology, renowned for its education and research in aeronautics, astronautics, and related technologies.
-
E.
ALE
ALE is a widely used research platform that provides a common interface to hundreds of Atari 2600 games for developing and evaluating artificial intelligence and reinforcement learning algorithms.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: AE Triple: [Ngawi Regency, hasVehicleRegistrationCode, AE]
Generated description
AE is an Indonesian vehicle registration code assigned to motor vehicles registered in Ngawi Regency and certain surrounding areas in East Java.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AE Target entity description: AE is an Indonesian vehicle registration code assigned to motor vehicles registered in Ngawi Regency and certain surrounding areas in East Java.
-
A.
AE
AE is the commonly used abbreviation for Academia Europaea, a European non-governmental association of scientists and scholars across all disciplines.
-
B.
AE
AE is the IATA airline designator assigned to Mandarin Airlines, a regional carrier based in Taiwan.
-
C.
AE
AE is the standard abbreviation for a DICOM Application Entity, which represents a logical device or software component that exchanges medical imaging data within a DICOM network.
-
D.
AE
AE is the Faculty of Aerospace Engineering at Delft University of Technology, renowned for its education and research in aeronautics, astronautics, and related technologies.
-
E.
ALE
ALE is a widely used research platform that provides a common interface to hundreds of Atari 2600 games for developing and evaluating artificial intelligence and reinforcement learning algorithms.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded64a2f24819099b21566756668a2 |
completed | April 15, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7e9078508190b5cbfe84125ba209 |
completed | May 9, 2026, 12:23 a.m. |
| NEDg | Description generation | batch_69fe83361ad08190b98523c2d171a11e |
completed | May 9, 2026, 12:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe83f4a8b08190913d42808acf694d |
completed | May 9, 2026, 12:46 a.m. |
Created at: April 10, 2026, 2:38 a.m.