Triple
T36620006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pawitter Kaur |
E903706
|
entity |
| Predicate | spouseHeldOfficeTitle |
P197342
|
FINISHED |
| Object | seventh President of India |
—
|
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: seventh President of India | Statement: [Pawitter Kaur, spouseHeldOfficeTitle, seventh President of India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseHeldOfficeTitle Context triple: [Pawitter Kaur, spouseHeldOfficeTitle, seventh President of India]
-
A.
spouseOffice
Indicates that one entity holds an office or position that is associated with, or held by, the spouse of another entity.
-
B.
spouseLaterOffice
Indicates that one person’s spouse held a particular office or position at a later time than the person in question.
-
C.
currentTitleHolderSpouseOf
Indicates that one entity is the current spouse of the individual who presently holds a specified title.
-
D.
spouseHeldOfficeNumber
chosen
Indicates that a person’s spouse held a specific numbered instance of a particular office or position (e.g., 1st, 2nd, 3rd holder of that office).
-
E.
spouseOfOfficeHolderJurisdiction
Indicates that one person is the spouse of a public office holder, with the relationship specifically tied to the jurisdiction in which that office is held.
- 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_69f76e6960e4819092047756ceb9a17e |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fe8ddf70e48190a917eb9e8f7b6966 |
completed | May 9, 2026, 1:29 a.m. |
| PD | Predicate disambiguation | batch_69fe87ef94dc81909bb00ec8d6de9bcd |
completed | May 9, 2026, 1:03 a.m. |
Created at: May 3, 2026, 4:11 p.m.