Triple
T19912618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Velódromo |
E478584
|
entity |
| Predicate | hasAdjacentStationOnLine9 |
P83323
|
FINISHED |
| Object | Mixiuhca |
—
|
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: Mixiuhca | Statement: [Velódromo, hasAdjacentStationOnLine9, Mixiuhca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mixiuhca Context triple: [Velódromo, hasAdjacentStationOnLine9, Mixiuhca]
-
A.
Mixiuhca
chosen
Mixiuhca is a Mexico City Metro station on Line 9 serving the eastern part of the city.
-
B.
Tenacatita
Tenacatita is a coastal area in Jalisco, Mexico, known for its beaches, calm bay, and laid-back tourist atmosphere along the Costa Alegre.
-
C.
Tezonco
Tezonco is a metro station in Mexico City that serves the southeastern area of the city on the capital’s rapid transit network.
-
D.
Ajusco
Ajusco is a prominent volcanic mountain and national park in southern Mexico City, known for its high elevation, forests, and popular outdoor recreation areas.
-
E.
Huehuetlán
Huehuetlán is a small town in the Huasteca region of San Luis Potosí, Mexico, known for its indigenous culture and lush tropical surroundings.
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659917fdc8190bf29bfdab0fe8f85 |
completed | April 20, 2026, 4:51 p.m. |
Created at: April 10, 2026, 1:53 p.m.