Triple
T17419429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pasaman Regency |
E423571
|
entity |
| Predicate | hasVehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
BA
BA is the vehicle registration code assigned to motor vehicles registered in Pasaman Regency, Indonesia.
|
E1268149
|
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: BA | Statement: [Pasaman Regency, hasVehicleRegistrationCode, BA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BA Context triple: [Pasaman Regency, hasVehicleRegistrationCode, BA]
-
A.
BA
BA is the New York Stock Exchange ticker symbol for The Boeing Company, a major American aerospace and defense manufacturer.
-
B.
BA
BA is a common abbreviation for Broken Arrow, a suburban city in northeastern Oklahoma.
-
C.
BA
BA is the station code for Bathurst station on the Toronto Transit Commission subway system.
-
D.
BA
BA is the former stock ticker symbol for Bell Aliant, a Canadian telecommunications company that provided internet, phone, and TV services primarily in Atlantic Canada before being acquired by Bell Canada.
-
E.
BA
BA is the station code for Balderas, a metro station in Mexico City’s rapid transit system.
- 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: BA Triple: [Pasaman Regency, hasVehicleRegistrationCode, BA]
Generated description
BA is the vehicle registration code assigned to motor vehicles registered in Pasaman Regency, Indonesia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: BA Target entity description: BA is the vehicle registration code assigned to motor vehicles registered in Pasaman Regency, Indonesia.
-
A.
BA
BA is the regional vehicle registration code assigned to motor vehicles registered in Pesisir Selatan Regency, Indonesia.
-
B.
BA
BA is the vehicle registration code assigned to motor vehicles registered in Agam Regency, Indonesia.
-
C.
BA
BA is the vehicle registration code used on license plates for the city and district of Bamberg in Upper Franconia, Germany.
-
D.
BA
BA is the vehicle registration code used on license plates for cars registered in Bratislava, the capital city of Slovakia.
-
E.
BA
BA is the station code for Bathurst station on the Toronto Transit Commission subway system.
- 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44236419c8190a106748bca6f30cd |
completed | April 19, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01a8041f548190a076b10516ccfced |
completed | May 11, 2026, 9:57 a.m. |
| NEDg | Description generation | batch_6a01a8d7e05c8190aceb0795a430fee7 |
completed | May 11, 2026, 10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01a943fdec8190a875c7eb56c742da |
completed | May 11, 2026, 10:02 a.m. |
Created at: April 10, 2026, 5:46 a.m.