Triple
T7782020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keene, California |
E221542
|
entity |
| Predicate | distanceToBakersfield |
P78976
|
FINISHED |
| Object | approximately 28 miles southeast |
—
|
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 28 miles southeast | Statement: [Keene, California, distanceToBakersfield, approximately 28 miles southeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBakersfield Context triple: [Keene, California, distanceToBakersfield, approximately 28 miles southeast]
-
A.
distanceFromLasVegas
Indicates the measured distance between a given place or object and the city of Las Vegas.
-
B.
distanceFromBarstow
Indicates the spatial distance between a given location and the reference point of Barstow.
-
C.
distanceToWinnemucca
Indicates the spatial distance between a given entity’s location and the location of Winnemucca.
-
D.
distanceToFresno
Indicates the physical distance between a given location or entity and the city of Fresno.
-
E.
distanceFromTucson
Indicates the spatial distance between a given entity and the location of Tucson.
- 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_69ca83ebbef881909ac47f789145fef7 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cae7e779ec8190b77296d9c2ac3210 |
completed | March 30, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69caa488532c819093ac40bba0b3c7ef |
completed | March 30, 2026, 4:27 p.m. |
| PDg | Predicate description generation | batch_69cae7e47c5c8190bca90d45b3cdc25e |
completed | March 30, 2026, 9:15 p.m. |
Created at: March 30, 2026, 4:21 p.m.