Triple
T17832535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West 215th Street |
E445294
|
entity |
| Predicate | usesNumberedStreetSystem |
P33926
|
FINISHED |
| Object | Manhattan numbered streets |
—
|
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: Manhattan numbered streets | Statement: [West 215th Street, usesNumberedStreetSystem, Manhattan numbered streets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesNumberedStreetSystem Context triple: [West 215th Street, usesNumberedStreetSystem, Manhattan numbered streets]
-
A.
hasStreetNumberingSystem
Indicates that a location or area uses an organized system for assigning numbers to buildings or addresses along its streets.
-
B.
isNumberedStreet
chosen
Indicates that a street is designated primarily by a number (e.g., "1st Street," "42nd Avenue") rather than by a proper name.
-
C.
hasRoadNumberSystem
Indicates that a place or region uses a specific system for assigning numbers to its roads or highways.
-
D.
hasJunctionNumbering
Indicates that a road or route is assigned a specific numbering system for its junctions or intersections.
-
E.
hasNumberOfStreets
Indicates the relationship that specifies how many streets are associated with or contained within a given entity.
- 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_69d8b9f1a6d881909f024bc603111cdb |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48d257414819088730f48ad7ab9ae |
completed | April 19, 2026, 8:07 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e266888190ae976b4b7d5b886f |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:15 a.m.