Triple
T5005451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Chief's Chief |
E112478
|
entity |
| Predicate | workSubjectPosition |
P60788
|
FINISHED |
| Object | defends Donald Trump |
—
|
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: defends Donald Trump | Statement: [The Chief's Chief, workSubjectPosition, defends Donald Trump]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workSubjectPosition Context triple: [The Chief's Chief, workSubjectPosition, defends Donald Trump]
-
A.
subjectPosition
Indicates the spatial or logical position of a subject relative to a reference frame, context, or other entities.
-
B.
workPosition
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.
subjectOfWork
Indicates that one entity is the main topic, focus, or theme that a particular work (such as a book, article, or artwork) is about.
-
E.
hasSubjectPosition
Indicates that an entity occupies or is assigned to a particular subject role or position within a structure, context, or organization.
- 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_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714cbc448190aa53a8a83d768b64 |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd73089f548190834103366e24ab40 |
completed | March 20, 2026, 4:17 p.m. |
Created at: March 20, 2026, 1:35 p.m.