Triple
T34943180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ensign Professor of Medicine at Yale University |
E1007781
|
entity |
| Predicate | chairHolderRole |
P182110
|
FINISHED |
| Object | physician-scientist |
—
|
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: physician-scientist | Statement: [Ensign Professor of Medicine at Yale University, chairHolderRole, physician-scientist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chairHolderRole Context triple: [Ensign Professor of Medicine at Yale University, chairHolderRole, physician-scientist]
-
A.
chairHolderField
Indicates that a field specifies or identifies the holder (person or entity) of a chair position.
-
B.
chairHolderStatus
Indicates the status or condition of an entity in relation to holding a specific chair or official position.
-
C.
chairperson
Indicates that one entity serves as the leader or head of a group, committee, or organization in relation to another entity.
-
D.
chairHolderStart
Indicates the point in time when an entity begins holding or occupying a chair position (such as an official or leadership role).
-
E.
namedChairAt
Indicates that a person holds a specific named chair or endowed professorship position at an institution.
- 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_69f76dc513fc819084a1ff52abbfa5bc |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69f7870dfe108190996c0c68630edc7f |
completed | May 3, 2026, 5:34 p.m. |
Created at: May 3, 2026, 4 p.m.