Triple
T6309359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierra Vista, Arizona |
E141460
|
entity |
| Predicate | distanceToTucson |
P67522
|
FINISHED |
| Object | about 75 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: about 75 miles southeast | Statement: [Sierra Vista, Arizona, distanceToTucson, about 75 miles southeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTucson Context triple: [Sierra Vista, Arizona, distanceToTucson, about 75 miles southeast]
-
A.
distanceFromTucson
chosen
Indicates the spatial distance between a given entity and the location of Tucson.
-
B.
distanceToPhoenix
Indicates the measured or estimated distance between a given entity’s location and the city of Phoenix.
-
C.
distanceToFlagstaff
Indicates the measured distance between a given entity’s location and the location of Flagstaff.
-
D.
distanceFromTijuana
Indicates the measured spatial distance between a given place or entity and the city of Tijuana.
-
E.
distanceFromAlbuquerque
Indicates the measured spatial distance between a given entity’s location and the city of Albuquerque.
- 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_69c008d00efc8190a36c05b4b4a3bf4b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0647f13a4819095c4ce8c42c5d1fb |
completed | March 22, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69c060e311b48190b1c74a5cf9435623 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:28 p.m.