Triple
T36910381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marblemount |
E912889
|
entity |
| Predicate | nearestTownTo |
P56555
|
FINISHED |
| Object | North Cascades National Park west entrance |
—
|
NE NERFINISHED |
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: North Cascades National Park west entrance | Statement: [Marblemount, nearestTownTo, North Cascades National Park west entrance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearestTownTo Context triple: [Marblemount, nearestTownTo, North Cascades National Park west entrance]
-
A.
nearestTownDistance
Indicates the distance from a given location to the closest town.
-
B.
nearestCityTo
Indicates that one city is the closest in distance to a given location or entity compared to all other cities.
-
C.
nearestTownCenter
chosen
Indicates that one location is the closest town center to another specified point or area.
-
D.
nearestInlandCity
Indicates that one city is the closest inland (non-coastal) city to another specified location.
-
E.
nearestCoastalTown
Indicates that one town is the closest coastal town geographically relative to a given reference location or town.
- 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_69f76e879768819085c2fb31a6a5b44b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fa0a7b00948190a257273d9968c5d7 |
completed | May 5, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69f9fec9c9488190ae2a349651a02782 |
completed | May 5, 2026, 2:29 p.m. |
Created at: May 3, 2026, 4:13 p.m.