Triple
T3679852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Diomede Island |
E78083
|
entity |
| Predicate | distanceToMainlandAlaska |
P5691
|
FINISHED |
| Object | about 40 kilometers |
—
|
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: about 40 kilometers | Statement: [Little Diomede Island, distanceToMainlandAlaska, about 40 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMainlandAlaska Context triple: [Little Diomede Island, distanceToMainlandAlaska, about 40 kilometers]
-
A.
distanceFromAnchorage
Indicates the measured distance between a given location or object and Anchorage.
-
B.
distanceFromMainland
chosen
Indicates the measured spatial separation between a location and the nearest point on the mainland.
-
C.
distanceFromFairbanks
Indicates the spatial distance between a given location or entity and the city of Fairbanks.
-
D.
distanceToPacificOcean
Indicates the physical distance between a given location or entity and the Pacific Ocean.
-
E.
distanceFromHonolulu
Indicates the spatial distance between a given location and Honolulu.
- 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_69ad85e18c1c8190be8aafb227f39f48 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc49039308190b33082e2b58aa5cf |
completed | March 8, 2026, 6:48 p.m. |
| PD | Predicate disambiguation | batch_69adb84be1fc81909721c871babb4633 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:25 p.m.