Triple
T24487449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marguerite Blake Wilbur Professor of Natural Science |
E617548
|
entity |
| Predicate | holderEmployer |
P7
|
FINISHED |
| Object | Stanford University |
—
|
NE NERFINISHED |
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: Stanford University | Statement: [Marguerite Blake Wilbur Professor of Natural Science, holderEmployer, Stanford University]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: holderEmployer Context triple: [Marguerite Blake Wilbur Professor of Natural Science, holderEmployer, Stanford University]
-
A.
employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
-
B.
parentEmployer
Indicates that one organization is the direct or higher-level employer of another organization or entity.
-
C.
employerRight
Indicates that an employer holds a specific right, entitlement, or legal authority in relation to an employee or employment situation.
-
D.
employer
chosen
Indicates a relationship where one entity hires, pays, and oversees the work of another entity.
-
E.
employerSide
Indicates that the subject participates in or represents the employer’s position, interests, or perspective within an employment relationship or dispute.
- 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_69e2d7f4e6bc8190aec540ae3b9ed7f2 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2a9d912e88190bc39c05a9d7f407e |
completed | April 30, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69f2a6a4580481908fddc385f5262f95 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:22 a.m.