Triple
T26247640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1992 United States House of Representatives elections |
E656492
|
entity |
| Predicate | chamberTermLength |
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: [1992 United States House of Representatives elections, chamberTermLength, 2 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chamberTermLength Context triple: [1992 United States House of Representatives elections, chamberTermLength, 2 years]
-
A.
termLength
Indicates the duration or period of time for which an agreement, position, or condition remains in effect.
-
B.
electsTermLength
chosen
Indicates the length of time for which an entity is elected to hold a particular position or office.
-
C.
parliamentaryTerm
Indicates the specific legislative session or fixed period of time during which a parliament is formally in office and exercises its authority.
-
D.
termLengthNumber
Indicates the numerical value representing the duration or length of a specified term.
-
E.
numberOfTermInOffice
Indicates the specific ordinal count of how many terms an entity has served in a particular office or position.
- 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_69ee5b4c59a881909d9ee4fd013fffd5 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69f60dc7d2a081908645d06c02dc3e02 |
completed | May 2, 2026, 2:44 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fd90fc81909055b211368f9139 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 26, 2026, 9:06 p.m.