Triple
T28421813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard J. Oglesby |
E719958
|
entity |
| Predicate | numberOfTermsInOfficeAsGovernorOfIllinois |
P17900
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Richard J. Oglesby, numberOfTermsInOfficeAsGovernorOfIllinois, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTermsInOfficeAsGovernorOfIllinois Context triple: [Richard J. Oglesby, numberOfTermsInOfficeAsGovernorOfIllinois, 3]
-
A.
governorTerm
Indicates the time period during which a person holds or held the office of governor of a specific jurisdiction.
-
B.
numberOfTermsAsGovernor
chosen
Indicates the number of separate terms an individual has served in the role of governor.
-
C.
servedAsGovernorNumber
Indicates the ordinal position in which an individual served as governor (e.g., first, second, third).
-
D.
servedAsGovernorUntil
Indicates that an entity held the position of governor up to a specified end date or time.
-
E.
numberOfTermInOffice
Indicates the specific ordinal count of how many terms an entity has served in a particular office or position.
- 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_69eff6f1c5088190bc24bfbf92f9c017 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69ff6ef0d61c81909162d37c15a1a3c3 |
completed | May 9, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69ff6c6a58e08190921317062cd9d489 |
completed | May 9, 2026, 5:18 p.m. |
Created at: April 28, 2026, 1:34 a.m.