Triple
T2610901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1000 Fifth Avenue, New York, NY |
E58768
|
entity |
| Predicate | hasStreetNumber |
P40967
|
FINISHED |
| Object | 1000 |
—
|
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: 1000 | Statement: [1000 Fifth Avenue, New York, NY, hasStreetNumber, 1000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetNumber Context triple: [1000 Fifth Avenue, New York, NY, hasStreetNumber, 1000]
-
A.
isNumberedStreet
Indicates that a street is designated primarily by a number (e.g., "1st Street," "42nd Avenue") rather than by a proper name.
-
B.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
-
C.
boroughNumber
Indicates the numerical identifier assigned to a specific borough within a larger administrative or municipal division.
-
D.
houseNumber
chosen
Indicates that an entity has a specific house or street number as part of its address.
-
E.
streetAddress
Indicates the specific location of an entity in terms of its numbered building and street name within a postal address.
- 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_69ab4ac3523881909679750c9f8c2dec |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd89325308190985598373eb0d296 |
completed | March 7, 2026, 7:49 a.m. |
| PD | Predicate disambiguation | batch_69abd80cd7fc81909e9696db2919129f |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.