Triple
T35284080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tennessee House of Representatives District 22 |
E1019025
|
entity |
| Predicate | termOfOfficeForRepresentative |
P540
|
FINISHED |
| Object | 2 years |
—
|
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 years | Statement: [Tennessee House of Representatives District 22, termOfOfficeForRepresentative, 2 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: termOfOfficeForRepresentative Context triple: [Tennessee House of Representatives District 22, termOfOfficeForRepresentative, 2 years]
-
A.
termOfOfficeResult
Indicates the outcome or status associated with a specific term of office, such as whether it was completed, successful, or ended in a particular way.
-
B.
hasTwoYearTermForRepresentative
Indicates that the representative’s term of office lasts for a duration of two years.
-
C.
termInOffice
Indicates the period during which an individual officially holds a particular office or position.
-
D.
numberOfTermInOffice
Indicates the specific ordinal count of how many terms an entity has served in a particular office or position.
-
E.
termLength
chosen
Indicates the duration or period of time for which an agreement, position, or condition remains in effect.
- 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_69f76de6d39c8190bb11342e4b91ff2b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78fdfca688190b2ae059009710566 |
completed | May 3, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69f78e2f52e08190a77661223a96c601 |
completed | May 3, 2026, 6:04 p.m. |
Created at: May 3, 2026, 4:03 p.m.