Triple
T12369245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Longview, Washington |
E294952
|
entity |
| Predicate | distanceToSeattleApproxKm |
P22795
|
FINISHED |
| Object | 200 |
—
|
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: 200 | Statement: [Longview, Washington, distanceToSeattleApproxKm, 200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToSeattleApproxKm Context triple: [Longview, Washington, distanceToSeattleApproxKm, 200]
-
A.
distanceToSeattle
Indicates the measured or calculated distance between a given entity’s location and the city of Seattle.
-
B.
distanceToAlaskaApproxKm
Indicates the approximate distance, measured in kilometers, between a given entity’s location and the state of Alaska.
-
C.
distanceToOlympia
Indicates the measured spatial distance between a given location or object and Olympia.
-
D.
distanceFromTacoma (miles)
Indicates the physical distance, measured in miles, between an entity’s location and the city of Tacoma.
-
E.
approximateDistanceKm
chosen
Indicates the estimated distance between two entities measured in kilometers, typically with some degree of inaccuracy or approximation.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d942a2d6e08190a13c7ff89af09354 |
completed | April 10, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69d93ecf6b548190a394b6b56a0c1c68 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.