Triple
T23297829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Begum Ayub Khan |
E590220
|
entity |
| Predicate | spousePositionStartTime |
P37616
|
FINISHED |
| Object | 1958 |
—
|
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: 1958 | Statement: [Begum Ayub Khan, spousePositionStartTime, 1958]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spousePositionStartTime Context triple: [Begum Ayub Khan, spousePositionStartTime, 1958]
-
A.
spouseStartTime
Indicates the point in time when two individuals began their spousal (marriage) relationship.
-
B.
spousePositionHeldStartTime
chosen
Indicates the date and time when a spouse first began holding a particular position or office.
-
C.
spouseEndTime
Indicates the time or date at which a spousal relationship between two entities ends.
-
D.
spouseOfficeEndTime
Indicates the time at which a spouse’s term or tenure in a particular office or position ends.
-
E.
roleDuringSpouseTenure
Indicates that a person held a particular role or position specifically during the period when their spouse was in office or serving in a defined tenure.
- 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.