Triple
T709102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port Authority of New York and New Jersey |
E14166
|
entity |
| Predicate | hasBoardMemberAppointmentBy |
P4954
|
FINISHED |
| Object | Governor of New York |
—
|
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: Governor of New York | Statement: [Port Authority of New York and New Jersey, hasBoardMemberAppointmentBy, Governor of New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoardMemberAppointmentBy Context triple: [Port Authority of New York and New Jersey, hasBoardMemberAppointmentBy, Governor of New York]
-
A.
membersAreAppointedIn
chosen
Indicates that the members of a group or body are selected or assigned to their positions within a particular organization, institution, or context.
-
B.
boardMember
Indicates that a person serves on the governing board of an organization, participating in its oversight and decision-making.
-
C.
memberHoldsOffice
Indicates that a member occupies or serves in a specific official position or office within an organization or governing body.
-
D.
committeeMember
Indicates that an entity serves as a member of a particular committee.
-
E.
hasAssociateMember
Indicates that an entity has another entity connected to it in a non-full, typically limited or secondary, membership capacity.
- 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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5c011948190b2cfccd8fe722742 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f0217081908268b3f47e72f8df |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.