Triple
T9779547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burque |
E237330
|
entity |
| Predicate | spellingVariant |
P457
|
FINISHED |
| Object | Burque |
E237330
|
NE FINISHED |
How this triple was built (2 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: Burque | Statement: [Burque, spellingVariant, Burque]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Burque Context triple: [Burque, spellingVariant, Burque]
-
A.
Burque
chosen
Burque is a colloquial nickname commonly used to refer to the city of Albuquerque, New Mexico.
-
B.
Velasco
Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
-
C.
Herrera
Herrera is a common Spanish surname borne by numerous notable figures across sports, politics, arts, and other fields in the Spanish-speaking world.
-
D.
Villacarlos
Villacarlos is the former name of Es Castell, a coastal town on the island of Menorca in Spain known for its natural harbor and military history.
-
E.
Tingo María
Tingo María is a city in central Peru known as the gateway to the Amazon and for its surrounding rainforest landscapes and national park.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca84d975a08190aab25b02a89bdab3 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda13663f081909b95563038eb6485 |
completed | April 1, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bd28b0e48190984cf44d88f324d7 |
completed | April 5, 2026, 1:38 a.m. |
Created at: March 30, 2026, 8:27 p.m.