Triple
T393786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Staten Island Ferry terminals |
E8935
|
entity |
| Predicate | doesNotAllow |
P12540
|
FINISHED |
| Object | private automobiles on ferries |
—
|
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: private automobiles on ferries | Statement: [Staten Island Ferry terminals, doesNotAllow, private automobiles on ferries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: doesNotAllow Context triple: [Staten Island Ferry terminals, doesNotAllow, private automobiles on ferries]
-
A.
doesNot
Indicates that a specified entity lacks, refrains from, or fails to perform a particular action or exhibit a particular property in relation to another entity or context.
-
B.
doesNotUse
Indicates that one entity intentionally refrains from employing, utilizing, or relying on another entity, method, or resource.
-
C.
doesNotProtect
Indicates that an entity fails to provide protection or safeguarding to another entity or object.
-
D.
doesNotAbolish
Indicates that one entity, action, or law does not eliminate, revoke, or put an end to another.
-
E.
doesNotHave
Indicates that one entity lacks, is missing, or is not in possession of another entity or attribute.
- 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec77a8a08190b6f96373aa8c1346 |
completed | Feb. 28, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69a2e96bd3848190a66ca14dfbd26da5 |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ea7d03a88190aab72e61d8673488 |
completed | Feb. 28, 2026, 1:15 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.