Triple
T7227701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yale University faculty |
E154822
|
entity |
| Predicate | employsPosition |
P47952
|
FINISHED |
| Object | department chair |
—
|
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: department chair | Statement: [Yale University faculty, employsPosition, department chair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employsPosition Context triple: [Yale University faculty, employsPosition, department chair]
-
A.
employedRole
Indicates that an entity holds or performs a specific role or position within an employment or work context.
-
B.
workPosition
chosen
Indicates the specific job role or position that an entity holds within an organization or workplace.
-
C.
positionInWork
Indicates the specific role, rank, or placement an entity holds within a larger work or structured composition.
-
D.
stateOfEmployment
Indicates that one entity’s employment status or condition is defined in relation to another entity (such as an employer, position, or employment situation).
-
E.
occupationDuringAlias
Indicates that an entity held a particular occupation specifically during the time period when it was known by a given alias.
- 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_69c68811dd1c8190ac460bb39e64e1f0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6e9df72cc81908d1c04e6e310fbb4 |
completed | March 27, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69c6e761b7fc8190857794d78af1b468 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:54 p.m.