Triple
T11687197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexico City Metro Line 2 |
E277773
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | San Cosme |
E445121
|
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: San Cosme | Statement: [Mexico City Metro Line 2, hasStation, San Cosme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Cosme Context triple: [Mexico City Metro Line 2, hasStation, San Cosme]
-
A.
San Cosme
chosen
San Cosme is a Mexico City Metro station on Line 2 that serves the San Rafael neighborhood near the historic center of the city.
-
B.
San Pascual
San Pascual is a coastal municipality in the province of Batangas in the Philippines, known for its mix of residential communities and industrial facilities.
-
C.
San Pascual
San Pascual is a coastal municipality in the Philippine province of Masbate known for its island landscapes and fishing-based local economy.
-
D.
San Juan de Flores
San Juan de Flores is a municipality in central Honduras known for its rural character and location within the Francisco Morazán Department.
-
E.
San Cristóbal de la Barranca
San Cristóbal de la Barranca is a small municipality in the state of Jalisco, Mexico, known for its deep canyon landscapes and hot springs along the Santiago River.
- 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4654be881909bd0256cf18e25de |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef14431f3c81908af9167c46f8c2bc |
completed | April 27, 2026, 7:46 a.m. |
Created at: April 8, 2026, 9:40 p.m.