Triple
T35924791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pat Quinn |
E1038989
|
entity |
| Predicate | officeStartForLieutenantGovernorOfIllinois |
P14741
|
FINISHED |
| Object | 2003 |
—
|
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: 2003 | Statement: [Pat Quinn, officeStartForLieutenantGovernorOfIllinois, 2003]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeStartForLieutenantGovernorOfIllinois Context triple: [Pat Quinn, officeStartForLieutenantGovernorOfIllinois, 2003]
-
A.
officeStartTime (Governor of Illinois)
Indicates the time at which the Governor of Illinois officially begins their term in office.
-
B.
officeEnd_LieutenantGovernor
Indicates the date or point in time when an individual’s term as Lieutenant Governor comes to an end.
-
C.
officeStartTime (Lieutenant Governor of Kansas)
Indicates the time at which the Lieutenant Governor of Kansas officially begins their term in office.
-
D.
officeStartTime (Lieutenant Governor of Pennsylvania)
Indicates the time at which the Lieutenant Governor of Pennsylvania officially begins their term in office.
-
E.
officeAssumedAsLieutenantGovernor
chosen
Indicates that an individual has formally taken on and begun serving in the role of lieutenant governor.
- 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_69f76e2320748190b7f5c4750d0cd0d3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a0004582bb08190b8d0b88251e8d333 |
completed | May 10, 2026, 4:06 a.m. |
| PD | Predicate disambiguation | batch_6a0003e3e5588190933beea5fb28f150 |
completed | May 10, 2026, 4:04 a.m. |
Created at: May 3, 2026, 4:07 p.m.