Triple
T30265277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 50th & France commercial district |
E769622
|
entity |
| Predicate | hasStreetIntersection |
P72012
|
FINISHED |
| Object | West 50th Street |
—
|
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: West 50th Street | Statement: [50th & France commercial district, hasStreetIntersection, West 50th Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetIntersection Context triple: [50th & France commercial district, hasStreetIntersection, West 50th Street]
-
A.
hasCrossStreets
chosen
Indicates that a location is situated at or near the intersection of the specified streets.
-
B.
crossesStreet
Indicates that an entity moves from one side of a street to the other, traversing the street’s width.
-
C.
atJunctionOf
Indicates that something is located at or directly connected to the point where two or more paths, roads, or lines meet.
-
D.
hasConnectingStreet
Indicates that two locations are linked by a street that directly connects them.
-
E.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
- 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_69f224856d9881908c7f0dd64f059672 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe38be079c8190a240191ac0e73e3a |
completed | May 8, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69fe350344508190930de2218156ca02 |
completed | May 8, 2026, 7:09 p.m. |
Created at: April 29, 2026, 7:43 p.m.