Triple
T22319936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Three Points, Arizona |
E551754
|
entity |
| Predicate | distanceToTucsonMiles |
P67522
|
FINISHED |
| Object | approximately 25 |
—
|
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 25 | Statement: [Three Points, Arizona, distanceToTucsonMiles, approximately 25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTucsonMiles Context triple: [Three Points, Arizona, distanceToTucsonMiles, approximately 25]
-
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.
distanceToPrescottInMiles
Indicates the numerical distance, measured in miles, between a given entity and Prescott.
-
E.
distanceToFlagstaff
Indicates the measured distance between a given entity’s location and the location of Flagstaff.
- 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15763bf0881908d859f85b4a6ce28 |
completed | April 29, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e73004d9e88190bb862319a5aea06b |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:42 p.m.