Triple
T31242436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seventh Avenue subway corridor |
E796597
|
entity |
| Predicate | hasBoroughSegment |
P192497
|
FINISHED |
| Object | Manhattan segment |
—
|
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 segment | Statement: [Seventh Avenue subway corridor, hasBoroughSegment, Manhattan segment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoroughSegment Context triple: [Seventh Avenue subway corridor, hasBoroughSegment, Manhattan segment]
-
A.
hasBorough
Indicates that one entity is located within, belongs to, or is administratively part of a specific borough.
-
B.
hasBoroughEndpoint
Indicates that something has an endpoint located within a specific borough.
-
C.
hasBoroughOrNeighborhood
Indicates that a place is located within, or associated with, a specific borough or neighborhood.
-
D.
hasBoroughCode
Indicates that an entity is associated with a specific borough identified by a particular code.
-
E.
hasBoroughEquivalent
Indicates that one administrative area corresponds functionally or hierarchically to a borough in another jurisdiction or classification system.
- 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_69f224db69ac81909a370adad6a7ac7c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69fd0d0aebac8190868a7714ddb4f1fd |
completed | May 7, 2026, 10:07 p.m. |
Created at: April 29, 2026, 9:11 p.m.