Triple
T22986140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Refinería |
E571611
|
entity |
| Predicate | isOnRouteBetween |
P24772
|
FINISHED |
| Object | Tacuba |
E60721
|
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: Tacuba | Statement: [Refinería, isOnRouteBetween, Tacuba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tacuba Context triple: [Refinería, isOnRouteBetween, Tacuba]
-
A.
Tacuba
chosen
Tacuba is a historic neighborhood in Mexico City known for its colonial-era architecture and role as a former pre-Hispanic town.
-
B.
Curridabat
Curridabat is a suburban city and canton in Costa Rica known for its residential neighborhoods, commercial development, and proximity to the capital, San José.
-
C.
Tecali
Tecali is a Mexican town renowned for its traditional crafts, particularly the production of Talavera pottery and stonework.
-
D.
Tecomán
Tecomán is a city in the Mexican state of Colima known for its agricultural production, particularly limes, and its proximity to Pacific coast beaches.
-
E.
Tuxpan
Tuxpan is a town and municipality in the Mexican state of Nayarit, known for its agricultural economy and traditional cultural festivals.
- 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_69e245b3c50481908bb3741ec9f40862 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182996ee08190ab74014ee7ecac2b |
completed | April 29, 2026, 4:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0bd376fff08190b35d33b0db8f2e8a |
completed | May 19, 2026, 3:05 a.m. |
Created at: April 17, 2026, 3:49 p.m.