Triple
T25024466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woodhaven Boulevard station |
E626669
|
entity |
| Predicate | hasCrossunderOrCrossover |
P37522
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Woodhaven Boulevard station, hasCrossunderOrCrossover, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrossunderOrCrossover Context triple: [Woodhaven Boulevard station, hasCrossunderOrCrossover, yes]
-
A.
hasCrossunders
Indicates that one entity passes beneath or under another entity, forming a crossing relationship where it goes below rather than above.
-
B.
hasCrossunder
chosen
Indicates that one entity passes or extends from one side to the other beneath another entity, forming an under-crossing relationship between them.
-
C.
hasCrossovers
Indicates that one entity features or participates in crossover appearances or interactions with another entity or set of entities.
-
D.
crossesUnder
Indicates that one entity passes beneath another entity’s path or structure, moving from one side to the other without intersecting it at the same elevation.
-
E.
hasCrossingPoint
Indicates that two or more entities intersect or share at least one common point in space or along their paths.
- 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_69e2ff28ee3881909c626af002457a4a |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cfb53f4819099bba48c5057e787 |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 18, 2026, 6:07 a.m.