Triple
T34899689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flushing Avenue |
E1006544
|
entity |
| Predicate | hasBoroughBoundaryNearby |
P16160
|
FINISHED |
| Object | Brooklyn–Queens border |
—
|
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: Brooklyn–Queens border | Statement: [Flushing Avenue, hasBoroughBoundaryNearby, Brooklyn–Queens border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoroughBoundaryNearby Context triple: [Flushing Avenue, hasBoroughBoundaryNearby, Brooklyn–Queens border]
-
A.
hasNearbyBorough
chosen
Indicates that one borough is geographically close to or adjacent to another borough.
-
B.
hasBoroughBorderContext
Indicates that a borough is contextually related to or influenced by the borders it shares with neighboring boroughs or areas.
-
C.
hasBoroughHallVicinity
Indicates that an entity is located in the area surrounding or in close proximity to a borough hall.
-
D.
hasBorough
Indicates that one entity is located within, belongs to, or is administratively part of a specific borough.
-
E.
hasBoroughOrNeighborhood
Indicates that a place is located within, or associated with, a specific borough or neighborhood.
- 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_69f76dbfe5788190ad8b64f241f470c8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd8e5f7c4c8190ab8e2f2a7bb1bd79 |
completed | May 8, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69fd8d8a16f08190b9e880901bfa44fe |
completed | May 8, 2026, 7:15 a.m. |
Created at: May 3, 2026, 4 p.m.