Triple
T10043606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xalisco |
E205355
|
entity |
| Predicate | distanceToTepic |
P91799
|
FINISHED |
| Object | approximately 7 kilometers |
—
|
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: approximately 7 kilometers | Statement: [Xalisco, distanceToTepic, approximately 7 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTepic Context triple: [Xalisco, distanceToTepic, approximately 7 kilometers]
-
A.
distanceFromMexicoCity
Indicates the measured distance between an entity’s location and Mexico City.
-
B.
distanceFromOaxacaCity
Indicates the spatial distance between a given place and Oaxaca City.
-
C.
distanceFromTijuana
Indicates the measured spatial distance between a given place or entity and the city of Tijuana.
-
D.
distanceToGuadalajara_km
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Guadalajara.
-
E.
distanceToMonterrey
Indicates the measured or specified distance between a given entity and the location of Monterrey.
- F. None of above. chosen
Provenance (4 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_69ca834f70e88190b2d74828b7767ec1 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcf61b3e08190b69bcf67b6a95342 |
completed | April 2, 2026, 2:07 a.m. |
| PD | Predicate disambiguation | batch_69cd4b8d2280819089de27e57babd1f3 |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd4f8d9b888190b8067bd916dae773 |
completed | April 1, 2026, 5:02 p.m. |
Created at: March 30, 2026, 8:55 p.m.