Triple
T5857543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Lemmon |
E130189
|
entity |
| Predicate | distanceFromTucson |
P67522
|
FINISHED |
| Object | approximately 30 miles northeast |
—
|
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 miles northeast | Statement: [Mount Lemmon, distanceFromTucson, approximately 30 miles northeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTucson Context triple: [Mount Lemmon, distanceFromTucson, approximately 30 miles northeast]
-
A.
distanceToPhoenix
Indicates the measured or estimated distance between a given entity’s location and the city of Phoenix.
-
B.
distanceFromAlbuquerque
Indicates the measured spatial distance between a given entity’s location and the city of Albuquerque.
-
C.
distanceFromLasVegas
Indicates the measured distance between a given place or object and the city of Las Vegas.
-
D.
distanceToFlagstaff
Indicates the measured distance between a given entity’s location and the location of Flagstaff.
-
E.
distanceFromTijuana
Indicates the measured spatial distance between a given place or entity and the city of Tijuana.
- 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_69c0084f3bb08190a7720f55f7aa4252 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03345ca0c819081c81148d054fed2 |
completed | March 22, 2026, 6:21 p.m. |
| PDg | Predicate description generation | batch_69c044a9c4f0819081b8c196932883f6 |
completed | March 22, 2026, 7:36 p.m. |
Created at: March 22, 2026, 3:56 p.m.