Triple
T37133802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dingmans Falls |
E919599
|
entity |
| Predicate | closestLargeUrbanArea |
P112043
|
FINISHED |
| Object | New York City |
—
|
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: New York City | Statement: [Dingmans Falls, closestLargeUrbanArea, New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: closestLargeUrbanArea Context triple: [Dingmans Falls, closestLargeUrbanArea, New York City]
-
A.
nearestLargeUrbanArea
chosen
Indicates that one entity is the closest major city or large urban center to the other entity.
-
B.
largestMetropolitanArea
Indicates that one entity is the largest metropolitan area associated with, contained within, or relevant to another entity, typically by population or spatial extent.
-
C.
largestCity
Indicates that one city is the most populous or significant urban center within a specified region or entity.
-
D.
largestCityOnItsEdge
Indicates that one city is the largest (by some measure, typically population) among all cities located on the boundary or edge of a given region or area.
-
E.
largestUrbanConcentrationIn
Indicates that an entity represents the biggest or most populous urban area located within a specified geographic region.
- 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_69f76e9d13e48190a108f7fbf80ff375 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
Created at: May 3, 2026, 4:15 p.m.