Triple
T2743532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States congressional districts in California |
E60808
|
entity |
| Predicate | hasRepresentationTermLength |
P540
|
FINISHED |
| Object | two-year term |
—
|
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: two-year term | Statement: [United States congressional districts in California, hasRepresentationTermLength, two-year term]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRepresentationTermLength Context triple: [United States congressional districts in California, hasRepresentationTermLength, two-year term]
-
A.
termLength
chosen
Indicates the duration or period of time for which an agreement, position, or condition remains in effect.
-
B.
termLengthNumber
Indicates the numerical value representing the duration or length of a specified term.
-
C.
hasTwoYearTermForRepresentative
Indicates that the representative’s term of office lasts for a duration of two years.
-
D.
electsTermLength
Indicates the length of time for which an entity is elected to hold a particular position or office.
-
E.
termLengthCondition
Indicates a condition or constraint specifying the required or allowed duration/length of a term (such as a contract, agreement, or period).
- 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_69ab4b79846081909096725374d65ce9 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb314410819095d4822f9277e6ff |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd829f1e88190aab1d54f87c69714 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:56 p.m.