Triple
T25189724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chilili, New Mexico |
E630830
|
entity |
| Predicate | distanceToAlbuquerqueInMiles |
P52892
|
FINISHED |
| Object | approximately 30 |
—
|
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 30 | Statement: [Chilili, New Mexico, distanceToAlbuquerqueInMiles, approximately 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToAlbuquerqueInMiles Context triple: [Chilili, New Mexico, distanceToAlbuquerqueInMiles, approximately 30]
-
A.
distanceFromAlbuquerque
chosen
Indicates the measured spatial distance between a given entity’s location and the city of Albuquerque.
-
B.
distanceToAmarillo
Indicates the spatial distance between a given entity and the location Amarillo.
-
C.
distanceFromAlamogordo
Indicates the spatial distance between a given entity and the location of Alamogordo.
-
D.
approximateDistanceToLasCruces
Indicates that an entity has an estimated or rough distance measurement to the location Las Cruces.
-
E.
distanceFromTucson
Indicates the spatial distance between a given entity and the location of Tucson.
- 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_69e75a8a6d088190ba1e82a4345225e7 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 21, 2026, 12:44 p.m.