Triple
T22385844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Valley, Arizona |
E553393
|
entity |
| Predicate | distanceTo Tucson, Arizona (kilometers) |
P67522
|
FINISHED |
| Object | approximately 32 |
—
|
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 32 | Statement: [Green Valley, Arizona, distanceTo Tucson, Arizona (kilometers), approximately 32]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceTo Tucson, Arizona (kilometers) Context triple: [Green Valley, Arizona, distanceTo Tucson, Arizona (kilometers), approximately 32]
-
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.
distanceToSedona
Indicates the measured or calculated spatial distance between a given entity’s location and the location of Sedona.
-
D.
distanceFromTijuana
Indicates the measured spatial distance between a given place or entity and the city of Tijuana.
-
E.
distanceFromToluca
Indicates the spatial distance between a given location and the city of Toluca.
- 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1582f5f348190881df0d5af110aef |
completed | April 29, 2026, 1 a.m. |
| PD | Predicate disambiguation | batch_69e73015484c8190a9a0b9f554b61a81 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:45 p.m.