Triple
T36531236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kearny Connection |
E900448
|
entity |
| Predicate | enablesServiceTo |
P6304
|
FINISHED |
| Object | Midtown Manhattan |
—
|
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: Midtown Manhattan | Statement: [Kearny Connection, enablesServiceTo, Midtown Manhattan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enablesServiceTo Context triple: [Kearny Connection, enablesServiceTo, Midtown Manhattan]
-
A.
enablesService
Indicates that one entity provides the capability or necessary conditions for another entity to offer or perform a specific service.
-
B.
operatesServiceTo
chosen
Indicates that one entity runs or provides a transportation or service route to another entity or location.
-
C.
serviceWith
Indicates that one entity provides or is associated with a particular service offered to or used by another entity.
-
D.
serviceFor
Indicates that one entity provides a service or performs functions on behalf of another entity.
-
E.
ledToOperationalServiceOf
Indicates that one entity caused or enabled another entity to enter or begin operational service.
- 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_69f76e5fbb388190b70c4c15573c8143 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b91fd88190ab85afd626603769 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:11 p.m.