Triple
T21027989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gornji Milanovac |
E517989
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
GM
GM is the vehicle registration code used on license plates for the municipality of Gornji Milanovac in Serbia.
|
E1463489
|
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: GM | Statement: [Gornji Milanovac, vehicleRegistrationCode, GM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GM Context triple: [Gornji Milanovac, vehicleRegistrationCode, GM]
-
A.
GM
GM is the post-nominal abbreviation used to denote recipients of the George Medal, a British civilian decoration for bravery.
-
B.
GM
GM is the vehicle registration code used on license plates for vehicles registered in the Oberbergischer Kreis district in North Rhine-Westphalia, Germany.
-
C.
GM
GM is the station code used to identify GMA Kamuning station in the Manila Metro Rail Transit system.
-
D.
GE
GE is the abbreviation for ICANN’s Government Engagement function, which manages and coordinates ICANN’s relationships and interactions with governments and intergovernmental organizations worldwide.
-
E.
GE
GE is the ISO 3166-1 alpha-2 country code for Georgia, a nation at the crossroads of Eastern Europe and Western Asia.
- 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: GM Triple: [Gornji Milanovac, vehicleRegistrationCode, GM]
Generated description
GM is the vehicle registration code used on license plates for the municipality of Gornji Milanovac in Serbia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: GM Target entity description: GM is the vehicle registration code used on license plates for the municipality of Gornji Milanovac in Serbia.
-
A.
GM
GM is the post-nominal abbreviation used to denote recipients of the George Medal, a British civilian decoration for bravery.
-
B.
GM
GM is the vehicle registration code used on license plates for vehicles registered in the Oberbergischer Kreis district in North Rhine-Westphalia, Germany.
-
C.
GM
GM is the station code used to identify GMA Kamuning station in the Manila Metro Rail Transit system.
-
D.
GE
GE is the abbreviation for ICANN’s Government Engagement function, which manages and coordinates ICANN’s relationships and interactions with governments and intergovernmental organizations worldwide.
-
E.
GE
GE is the ISO 3166-1 alpha-2 country code for Georgia, a nation at the crossroads of Eastern Europe and Western Asia.
- 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_69e0b503275c8190afd9a163f997c709 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc7efda081909a4de1c389166bf2 |
completed | April 21, 2026, 4:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a094743553c81908a029cdfe9376bbd |
completed | May 17, 2026, 4:42 a.m. |
| NEDg | Description generation | batch_6a0947d293588190a235ff9713b7630f |
completed | May 17, 2026, 4:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0948839fd481909a68a1e7105d9b72 |
completed | May 17, 2026, 4:48 a.m. |
Created at: April 16, 2026, 1:55 p.m.