Triple
T22293866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Lemmon Observatory |
E551066
|
entity |
| Predicate | distanceToNearestCity |
P78268
|
FINISHED |
| Object | approximately 45 kilometers from Tucson |
—
|
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 45 kilometers from Tucson | Statement: [Mount Lemmon Observatory, distanceToNearestCity, approximately 45 kilometers from Tucson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToNearestCity Context triple: [Mount Lemmon Observatory, distanceToNearestCity, approximately 45 kilometers from Tucson]
-
A.
nearestCityTo
Indicates that one city is the closest in distance to a given location or entity compared to all other cities.
-
B.
nearestTownDistance
Indicates the distance from a given location to the closest town.
-
C.
distanceFromMajorCity
Indicates the measured distance between a given location and a specified major city.
-
D.
nearestCityCenterDistance
chosen
Indicates the distance from a given location to the closest city center.
-
E.
distanceFromRegionalCapital
Indicates the measured spatial distance between a given place and its corresponding regional capital.
- 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_69e11e45fb848190a1b2ae21296e3a5f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1560de3508190951ad0806ae3cc0d |
completed | April 29, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69e72ffa438481908f80879aef2a589b |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:41 p.m.