Triple
T31319191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tasqueña Metro station complex |
E798678
|
entity |
| Predicate | locatedInDirectionFromCityCenter |
P28261
|
FINISHED |
| Object | south of Mexico City historic center |
—
|
LITERAL 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: south of Mexico City historic center | Statement: [Tasqueña Metro station complex, locatedInDirectionFromCityCenter, south of Mexico City historic center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInDirectionFromCityCenter Context triple: [Tasqueña Metro station complex, locatedInDirectionFromCityCenter, south of Mexico City historic center]
-
A.
directionFromCityCenter
chosen
Indicates the compass direction in which one location lies relative to the city center.
-
B.
distanceFromCityCenterDirection
Indicates the distance and compass direction of a location relative to the center of a specified city.
-
C.
directionFromCityCentre
Indicates the compass direction in which one location lies relative to the city centre.
-
D.
isFartherFromCityCenterThan
Indicates that one location is at a greater distance from the city center than another location.
-
E.
roadDistanceToCityCentre_km
Indicates the distance in kilometers from a location to the city centre when traveling by road.
- F. None of above.
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_69f224e1932c81908fef14f7b03a10b7 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a017d27e184819094638c3cf6876de4 |
completed | May 11, 2026, 6:54 a.m. |
| PD | Predicate disambiguation | batch_6a017c785a44819083111384b55769e9 |
completed | May 11, 2026, 6:51 a.m. |
Created at: April 29, 2026, 9:15 p.m.