Triple
T8709037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stuart Ullman |
E206725
|
entity |
| Predicate | offersJobAs |
P26127
|
FINISHED |
| Object | winter caretaker |
—
|
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: winter caretaker | Statement: [Stuart Ullman, offersJobAs, winter caretaker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersJobAs Context triple: [Stuart Ullman, offersJobAs, winter caretaker]
-
A.
offersOpportunity
Indicates that one entity provides another with a chance or possibility to do, obtain, or experience something.
-
B.
offersProcess
Indicates that one entity provides or makes available a particular process for use by another entity.
-
C.
offeredPosition
chosen
Indicates that one entity has extended a job or role opportunity to another entity.
-
D.
offering
Indicates that one entity presents or provides something to another entity, typically as a gift, contribution, or proposal.
-
E.
offersApprenticeshipTraining
Indicates that one entity provides apprenticeship-based training opportunities or programs to another entity.
- 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_69ca835645e881908f00e3c8b51da81d |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5c2e9c688190aceefaa2c3b7d7bd |
completed | March 31, 2026, 11:43 p.m. |
| PD | Predicate disambiguation | batch_69cc456bda508190a9aa0fb92760739e |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:35 p.m.