Triple
T23297823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Begum Ayub Khan |
E590220
|
entity |
| Predicate | roleDuringTenure |
P37119
|
FINISHED |
| Object | hosted state functions |
—
|
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: hosted state functions | Statement: [Begum Ayub Khan, roleDuringTenure, hosted state functions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleDuringTenure Context triple: [Begum Ayub Khan, roleDuringTenure, hosted state functions]
-
A.
roleDuringOccupation
Indicates the specific role or position an entity held during a particular occupation or period of control.
-
B.
namedAfterOccupationOrRole
Indicates that an entity is named after a specific occupation, profession, or social role associated with a person or group.
-
C.
economicRolePast
Indicates that an entity previously held a specific economic function, position, or role in the past.
-
D.
roleInExperience
Indicates the specific function, position, or part an entity plays within a particular experience or event.
-
E.
servedInRole
chosen
Indicates that one entity performed duties or held a position within a specified role or office in relation 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_69e25d1c0ecc8190a355aa229f06d0e0 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196d083188190abaae77dd4cf2bae |
completed | April 29, 2026, 5:27 a.m. |
| PD | Predicate disambiguation | batch_69effcf325f88190b320268c3c551abb |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 5:03 p.m.