Triple
T5316006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mosholu Parkway |
E119148
|
entity |
| Predicate | hasCrossovers |
P63455
|
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: [Mosholu Parkway, hasCrossovers, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrossovers Context triple: [Mosholu Parkway, hasCrossovers, yes]
-
A.
hasCrossoverHits
Indicates that an entity (such as an artist or work) has achieved significant success across multiple distinct genres, markets, or audience categories.
-
B.
crossesOverWith
Indicates that one entity intersects or overlaps with another, typically by passing across or through its path, boundary, or extent.
-
C.
hasCross
Indicates that one entity possesses, displays, or is marked by a cross in relation to another entity or context.
-
D.
hasNumberOfCrosses
Indicates the quantity of crosses associated with or present on a given entity.
-
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. chosen
Provenance (4 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_69bd446b57bc8190a513d2e6c40314f3 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd86f20f008190be7b5848af05f2b8 |
completed | March 20, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69bd84534f9c8190bc19d4812060768d |
completed | March 20, 2026, 5:30 p.m. |
| PDg | Predicate description generation | batch_69bd86f0cbfc8190b6665dd9b28d6345 |
completed | March 20, 2026, 5:42 p.m. |
Created at: March 20, 2026, 1:54 p.m.