Triple
T9700635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States House of Representatives elections |
E234765
|
entity |
| Predicate | hasTermLengthForWinners |
P39902
|
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: [United States House of Representatives elections, hasTermLengthForWinners, 2 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTermLengthForWinners Context triple: [United States House of Representatives elections, hasTermLengthForWinners, 2 years]
-
A.
termLengthCondition
Indicates a condition or constraint specifying the required or allowed duration/length of a term (such as a contract, agreement, or period).
-
B.
termLength
Indicates the duration or period of time for which an agreement, position, or condition remains in effect.
-
C.
electsTermLength
chosen
Indicates the length of time for which an entity is elected to hold a particular position or office.
-
D.
termLengthNumber
Indicates the numerical value representing the duration or length of a specified term.
-
E.
hasFixedTermElections
Indicates that elections for a given office or body occur at predetermined, regular intervals rather than being called flexibly or at variable times.
- 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_69ca84cb580c8190a7e5f4b3bcdaf2a4 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d70f55c8190934f37c25e9d4ba4 |
completed | April 1, 2026, 10:34 p.m. |
| PD | Predicate disambiguation | batch_69cd03b641408190942464eaf174c6b5 |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:18 p.m.