Triple
T31901214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dalberg-Acton |
E814426
|
entity |
| Predicate | bearerOccupationAssociation |
P93726
|
FINISHED |
| Object | historian |
—
|
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: historian | Statement: [Dalberg-Acton, bearerOccupationAssociation, historian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bearerOccupationAssociation Context triple: [Dalberg-Acton, bearerOccupationAssociation, historian]
-
A.
occupationOfAssociatedPerson
Indicates the job or professional role held by a person who is associated with another referenced entity.
-
B.
occupationOfBearer
chosen
Indicates that a specified occupation or job role is held by the bearer entity.
-
C.
occupationalAssociation
Indicates a relationship where one entity is connected to another through a job, profession, or work-related role.
-
D.
isAssociatedWithProfessionOfBearer
Indicates that one entity is connected to, or involved with, the profession or occupational role held by another entity.
-
E.
endedOccupationOf
Indicates that one entity brought another entity’s occupation or control of a place or position to an end.
- 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_69f348f04d7881909537fc9e7cbc670e |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 30, 2026, 11:59 p.m.