Triple
T19040973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Livengood |
E465998
|
entity |
| Predicate | distanceToFairbanksInMiles |
P49332
|
FINISHED |
| Object | about 80 |
—
|
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 80 | Statement: [Livengood, distanceToFairbanksInMiles, about 80]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToFairbanksInMiles Context triple: [Livengood, distanceToFairbanksInMiles, about 80]
-
A.
distanceFromFairbanks
chosen
Indicates the spatial distance between a given location or entity and the city of Fairbanks.
-
B.
distanceFromAnchorage
Indicates the measured distance between a given location or object and Anchorage.
-
C.
distanceFromMurmansk
Indicates the spatial distance between a given location and the city of Murmansk.
-
D.
approximateDistanceFromAnchorage
Indicates the estimated spatial distance between a given entity and Anchorage, rather than an exact measured value.
-
E.
distanceToAlaskaApproxKm
Indicates the approximate distance, measured in kilometers, between a given entity’s location and the state of Alaska.
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d80054c88190a9d3a49aed504235 |
completed | April 20, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69e4a3001e388190aa6057266514e75a |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:02 p.m.