Triple
T5025673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Redoubt |
E112967
|
entity |
| Predicate | distanceToAnchorage |
P43986
|
FINISHED |
| Object | approximately 170 km southwest |
—
|
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 170 km southwest | Statement: [Mount Redoubt, distanceToAnchorage, approximately 170 km southwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToAnchorage Context triple: [Mount Redoubt, distanceToAnchorage, approximately 170 km southwest]
-
A.
distanceFromAnchorage
chosen
Indicates the measured distance between a given location or object and Anchorage.
-
B.
distanceFromFairbanks
Indicates the spatial distance between a given location or entity and the city of Fairbanks.
-
C.
distanceToAlaskaApproxKm
Indicates the approximate distance, measured in kilometers, between a given entity’s location and the state of Alaska.
-
D.
distanceToSeattle
Indicates the measured or calculated distance between a given entity’s location and the city of Seattle.
-
E.
distanceToSapporo
Indicates the measured or calculated distance between a given entity and the location of Sapporo.
- 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd736a0f8c819091d06275954329e9 |
completed | March 20, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69bd71509e9c8190a60c1d8d04936a12 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:36 p.m.