Triple
T11687213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexico City Metro Line 2 |
E277773
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Tasqueña |
E226659
|
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: Tasqueña | Statement: [Mexico City Metro Line 2, hasStation, Tasqueña]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tasqueña Context triple: [Mexico City Metro Line 2, hasStation, Tasqueña]
-
A.
Tasqueña
chosen
Tasqueña is a major transit hub and southern terminus of Mexico City’s Metro Line 2, integrating metro, light rail, and bus services.
-
B.
Tamuín
Tamuín is a municipality in the Mexican state of San Luis Potosí, known for its Huastec cultural heritage and proximity to important archaeological and natural sites.
-
C.
Tagüeña
Tagüeña is a Spanish surname most notably associated with Manuel Tagüeña, a Republican military officer and physicist active during the Spanish Civil War.
-
D.
Bañuela
Bañuela is the highest peak in Spain’s Sierra Morena mountain range, located in the southern part of the Iberian Peninsula.
-
E.
Requena
Requena is a small Peruvian city in the Loreto region, known as a remote Amazonian river port and gateway to surrounding rainforest communities.
- 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_69f01943196c8190900b46da238e1f24 |
completed | April 28, 2026, 2:19 a.m. |
Created at: April 8, 2026, 9:40 p.m.