Triple
T29499859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | O. Panneerselvam |
E748335
|
entity |
| Predicate | hasBeenInOffice |
P88319
|
FINISHED |
| Object | 21st century |
—
|
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: 21st century | Statement: [O. Panneerselvam, hasBeenInOffice, 21st century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeenInOffice Context triple: [O. Panneerselvam, hasBeenInOffice, 21st century]
-
A.
succeededInOffice
Indicates that one officeholder directly followed another in holding the same official position.
-
B.
hasLeaderHeldOffice
chosen
Indicates that the specified leader has occupied or served in an official office or position.
-
C.
hasBeenInGovernmentUntil
Indicates that an entity held a government position continuously up to a specified end time or date.
-
D.
heldPoliticalOfficeIn
Indicates that an entity served in a political office or position within a specified governmental body or jurisdiction.
-
E.
remainedInOfficeAs
Indicates that one entity continued to hold the same official position or role as another entity, without interruption, over a given period.
- 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_69f0bd455a9c8190b40a3e8ea38cf61f |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f71f8ee0688190bd025f27993452d3 |
completed | May 3, 2026, 10:12 a.m. |
| PD | Predicate disambiguation | batch_69f71cc405c08190863565609a4c8499 |
completed | May 3, 2026, 10 a.m. |
Created at: April 28, 2026, 4:22 p.m.