Triple
T20601276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Field, British Columbia |
E506185
|
entity |
| Predicate | distanceToGolden_km |
P140727
|
FINISHED |
| Object | approximately 57 |
—
|
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 57 | Statement: [Field, British Columbia, distanceToGolden_km, approximately 57]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToGolden_km Context triple: [Field, British Columbia, distanceToGolden_km, approximately 57]
-
A.
distanceToBega_km
Indicates the physical distance, measured in kilometers, between a given location and Bega.
-
B.
distanceFromGizaPlateau
Indicates the measured spatial distance between a given location and the Giza Plateau.
-
C.
lengthInKm
Indicates that one entity specifies the length or distance of another entity measured in kilometers.
-
D.
tourDistanceApproxKm
Indicates an approximate total distance, measured in kilometers, covered during a tour or journey.
-
E.
distanceFromGori
Indicates the spatial distance between a given entity or location and the place named Gori.
- 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_69e0b4ba6ae88190af871e1f9522c704 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa1ffd088190adeacb9fe4907530 |
completed | April 20, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69e59fffe1748190825e4eaa90340631 |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a9f3f88190b961db9aca36f7da |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:41 a.m.