Triple
T1892755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AG |
E41907
|
entity |
| Predicate | officeItAbbreviatesReportsTo |
P33113
|
FINISHED |
| Object | President of the United States |
—
|
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: President of the United States | Statement: [AG, officeItAbbreviatesReportsTo, President of the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeItAbbreviatesReportsTo Context triple: [AG, officeItAbbreviatesReportsTo, President of the United States]
-
A.
officeTerm
Indicates the period of time during which an individual officially holds a particular position or office.
-
B.
office
Indicates that an entity holds or occupies an official position, role, or post within an organization or institution.
-
C.
worksWithOffice
Indicates that an entity collaborates or is professionally associated with a particular office or office-based organization.
-
D.
equivalentOffice
Indicates that two offices are considered functionally or formally the same position, role, or authority, even if they differ in name or jurisdiction.
-
E.
relatesToOffice
Indicates that one entity has a connection, association, or relevance to an office, its functions, or its environment.
- 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.