Triple
T1892758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AG |
E41907
|
entity |
| Predicate | officeItAbbreviatesRole |
P33116
|
FINISHED |
| Object | chief law enforcement officer of the federal government |
—
|
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: chief law enforcement officer of the federal government | Statement: [AG, officeItAbbreviatesRole, chief law enforcement officer of the federal government]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeItAbbreviatesRole Context triple: [AG, officeItAbbreviatesRole, chief law enforcement officer of the federal government]
-
A.
worksWithOffice
Indicates that an entity collaborates or is professionally associated with a particular office or office-based organization.
-
B.
officeIsIn
Indicates that one office is located within or inside another specified place or building.
-
C.
office
Indicates that an entity holds or occupies an official position, role, or post within an organization or institution.
-
D.
includedOffice
Indicates that one office is contained within, or forms part of, another office or organizational unit.
-
E.
officeTerm
Indicates the period of time during which an individual officially holds a particular position or office.
- 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_69a8864b6de0819098d089f6a1b910a7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb1480a6c81909fcf5cce4c42fed4 |
completed | March 7, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69abafe61bc48190ac9ead027df930e1 |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb11bfd2c8190a805372589f73238 |
completed | March 7, 2026, 5:01 a.m. |
Created at: March 4, 2026, 7:34 p.m.