Triple
T7754852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Center Drive |
E175865
|
entity |
| Predicate | hasUseRegulation |
P68074
|
FINISHED |
| Object | subject to Central Park traffic rules |
—
|
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: subject to Central Park traffic rules | Statement: [Center Drive, hasUseRegulation, subject to Central Park traffic rules]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUseRegulation Context triple: [Center Drive, hasUseRegulation, subject to Central Park traffic rules]
-
A.
hasRegulations
Indicates that one entity imposes, contains, or is associated with rules or regulatory requirements that govern the behavior or operation of another entity.
-
B.
regulatesUse
Indicates that one entity controls, governs, or sets rules for how another entity may be used.
-
C.
supportsRegulation
Indicates that one entity endorses, backs, or advocates for the implementation or continuation of a specific regulation.
-
D.
hasRegulatedBy
chosen
Indicates that one entity is subject to control, governance, or rules imposed by another entity.
-
E.
allowsRegulationOf
Indicates that one entity grants the authority, means, or conditions for another entity to control, manage, or govern something.
- 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_69c6996180088190832e38e8d83ff54a |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c705257ca08190a78c592a1e616da8 |
completed | March 27, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69c7016df2b08190b2330a2010691431 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:08 p.m.