Triple
T3269591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Dailey |
E68610
|
entity |
| Predicate | officeHeldInThePast |
P25590
|
FINISHED |
| Object | local government office in Leon County, Florida |
—
|
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: local government office in Leon County, Florida | Statement: [John Dailey, officeHeldInThePast, local government office in Leon County, Florida]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHeldInThePast Context triple: [John Dailey, officeHeldInThePast, local government office in Leon County, Florida]
-
A.
officeHeldDuring
Indicates that a person occupied a specific official position during a particular time period.
-
B.
officeHeldIn
chosen
Indicates that a particular office or position is held within or associated with a specific geographic or administrative location.
-
C.
officeHeldOf
Indicates that a specific office or position is (or was) held by a particular person or entity.
-
D.
officeHeldInPeriod
Indicates that an entity held a particular office or position during a specified time period.
-
E.
officeHeldUnder
Indicates that one entity holds or has held an official position, role, or office under the authority, jurisdiction, or administration of another entity.
- 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_69ad859b54f881909bf530d549caf2fd |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafd0eddc8190834a64f6b8e8e9f9 |
completed | March 8, 2026, 5:20 p.m. |
| PD | Predicate disambiguation | batch_69ada41d7eac8190ada4bf5f793d5c49 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:09 p.m.