Triple
T7548734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chaudhry Muhammad Ali |
E178472
|
entity |
| Predicate | precedenceInOffice |
P2953
|
FINISHED |
| Object | fourth Prime Minister of Pakistan |
—
|
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: fourth Prime Minister of Pakistan | Statement: [Chaudhry Muhammad Ali, precedenceInOffice, fourth Prime Minister of Pakistan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: precedenceInOffice Context triple: [Chaudhry Muhammad Ali, precedenceInOffice, fourth Prime Minister of Pakistan]
-
A.
ordinalInOffice
chosen
Indicates the numerical order or rank of an individual’s term or tenure in a particular office or position.
-
B.
previousOffice
Indicates that one office or position was held immediately before another in a sequence of offices.
-
C.
precededByOfficeTitle
Indicates that one office title directly came before another in an ordered sequence of office positions.
-
D.
natureOfOffice
Indicates the type or character of an office or position, specifying what kind of role or function it represents.
-
E.
typeOfOffice
Indicates the specific category or kind of office that an office entity belongs to (e.g., executive, legislative, judicial, or other office types).
- 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_69c69f2cbe08819088f9eb0c03ef529b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f89b9afc8190b3e61a8e2cea7ad7 |
completed | March 27, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69c6f4daad6c8190af2b8ae88d2c8cb7 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:49 p.m.