Triple
T13227094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fifth Avenue |
E314908
|
entity |
| Predicate | hasNumberingRole |
P108614
|
FINISHED |
| Object | divides Manhattan east and west street addresses |
—
|
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: divides Manhattan east and west street addresses | Statement: [Fifth Avenue, hasNumberingRole, divides Manhattan east and west street addresses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberingRole Context triple: [Fifth Avenue, hasNumberingRole, divides Manhattan east and west street addresses]
-
A.
isNumberedBy
Indicates that an entity is assigned, identified, or organized by a specific number or numbering scheme.
-
B.
hasCategoryNumbering
Indicates that an entity is assigned or associated with a specific category-based numbering or index within a classification system.
-
C.
isNumbered
Indicates that an entity has been assigned a specific number or position in an ordered sequence.
-
D.
includesNumberingRange
Indicates that one entity contains or covers a specified contiguous range of numbers associated with another entity.
-
E.
numberingType
Indicates the scheme or style used to assign sequential numbers or labels within an ordered set.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d3232d48190a3c792b025c596a6 |
completed | April 10, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69d98bcb21648190aef241de1e7887e2 |
completed | April 10, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69d98c959ba08190adf29dc0c4e1fca6 |
completed | April 10, 2026, 11:49 p.m. |
Created at: April 9, 2026, 9:21 p.m.