Triple
T34898643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buena Vista |
E1006511
|
entity |
| Predicate | distanceToSaltillo |
P205599
|
FINISHED |
| Object | approximately 12 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 12 kilometers | Statement: [Buena Vista, distanceToSaltillo, approximately 12 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToSaltillo Context triple: [Buena Vista, distanceToSaltillo, approximately 12 kilometers]
-
A.
distanceToSaltillo_km
Indicates the distance, measured in kilometers, between a given place or entity and Saltillo.
-
B.
distanceToMonterrey
Indicates the measured or specified distance between a given entity and the location of Monterrey.
-
C.
distanceFromMexicoCity
Indicates the measured distance between an entity’s location and Mexico City.
-
D.
distanceToTepic
Indicates the spatial distance between an entity and the location Tepic.
-
E.
distanceToGuadalajara_km
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Guadalajara.
- 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_69f76dbfe5788190ad8b64f241f470c8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4 p.m.