Triple
T31066349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1938 United States House of Representatives elections |
E791680
|
entity |
| Predicate | republicanSeatsAfter |
P89207
|
FINISHED |
| Object | 169 |
—
|
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: 169 | Statement: [1938 United States House of Representatives elections, republicanSeatsAfter, 169]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: republicanSeatsAfter Context triple: [1938 United States House of Representatives elections, republicanSeatsAfter, 169]
-
A.
numberOfRepublicanMembers
chosen
Indicates the quantity of members in a group or body who are affiliated with or belong to the Republican Party.
-
B.
afterElectionSenator
Indicates that one person holds the position of senator following a specified election.
-
C.
netSeatChangeForRepublicanParty
Indicates the overall gain or loss in the number of seats held by the Republican Party after an election or series of elections.
-
D.
republicanParty
Indicates that an entity is affiliated with, belongs to, or is a member/supporter of the Republican Party.
-
E.
ConservativeSeatsWon
Indicates the number of parliamentary or legislative seats won by the Conservative party in an election.
- 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_69f224cc0c5c81908404f087bff92997 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f697eabb048190bc01a830f14942c6 |
completed | May 3, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_69f69664142c8190bc695501056b0236 |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 9:01 p.m.