Triple
T23255968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jimmie Davis |
E581869
|
entity |
| Predicate | numberOfTermsAsGovernorOfLouisiana |
P17900
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Jimmie Davis, numberOfTermsAsGovernorOfLouisiana, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTermsAsGovernorOfLouisiana Context triple: [Jimmie Davis, numberOfTermsAsGovernorOfLouisiana, 2]
-
A.
numberOfTermsAsGovernor
chosen
Indicates the number of separate terms an individual has served in the role of governor.
-
B.
numberOfGovernors
Indicates the total count of governors associated with or governing a specified entity.
-
C.
endTimeAsGovernorOfLouisiana
Indicates the date and time at which an individual's tenure as Governor of Louisiana concludes.
-
D.
servedAsGovernorNumber
Indicates the ordinal position in which an individual served as governor (e.g., first, second, third).
-
E.
governorTerm
Indicates the time period during which a person holds or held the office of governor of a specific jurisdiction.
- 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_69e246079f58819085eaa9c260906880 |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f194c4905c819099ca21c6529413ac |
completed | April 29, 2026, 5:19 a.m. |
| PD | Predicate disambiguation | batch_69effce4d704819092826931d430e8c4 |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:11 p.m.