Triple
T36625294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stewart Crossing |
E904152
|
entity |
| Predicate | distanceToWhitehorse_km |
P136594
|
FINISHED |
| Object | approx. 286 |
—
|
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: approx. 286 | Statement: [Stewart Crossing, distanceToWhitehorse_km, approx. 286]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToWhitehorse_km Context triple: [Stewart Crossing, distanceToWhitehorse_km, approx. 286]
-
A.
distanceToWhitehorse
chosen
Indicates the measured distance between a given entity’s location and the location of Whitehorse.
-
B.
roadDistanceToWhitehorse
Indicates the distance between an entity and Whitehorse when traveling via roads rather than in a straight line.
-
C.
distanceToTofino_km
Indicates the distance, measured in kilometers, between a given location and Tofino.
-
D.
distanceFromKetchikan
Indicates the spatial distance between a given location and the city of Ketchikan.
-
E.
distanceToIqaluit
Indicates the spatial distance between a given entity’s location and the location of Iqaluit.
- 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_69f76e6ae750819096911e6e2d4d12c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:11 p.m.