Triple
T20157857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metro de la Ciudad de México |
E491620
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object | Línea 1 |
—
|
NE NERFINISHED |
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: Línea 1 | Statement: [Metro de la Ciudad de México, hasLine, Línea 1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Línea 1 Context triple: [Metro de la Ciudad de México, hasLine, Línea 1]
-
A.
Metro Line 1
chosen
Metro Line 1 is a primary rapid transit route in its city's metro system, serving as a major corridor for passenger travel and interchanges with other lines.
-
B.
Main Line 1
Main Line 1 is a major railway corridor in Pakistan that serves as a key route for passenger and freight trains across the country.
-
C.
Línea 2
Línea 2 is a metro line that forms part of an urban rapid transit network and connects with other lines, including Línea 6, at designated interchange stations.
-
D.
Línea 6
Línea 6 is a modern, fully automated metro line in Santiago, Chile, known for its advanced technology, safety features, and connection between key residential and commercial areas of the city.
-
E.
Línea 6
Línea 6 is a circular line of the Madrid Metro that loops around the city, connecting many major transfer stations and neighborhoods.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667e18a0c8190a2cc2b305da28047 |
completed | April 20, 2026, 5:52 p.m. |
Created at: April 11, 2026, 11:34 p.m.