Triple
T31066347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1938 United States House of Representatives elections |
E791680
|
entity |
| Predicate | republicanSeatsBefore |
P89207
|
FINISHED |
| Object | 88 |
—
|
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: 88 | Statement: [1938 United States House of Representatives elections, republicanSeatsBefore, 88]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: republicanSeatsBefore Context triple: [1938 United States House of Representatives elections, republicanSeatsBefore, 88]
-
A.
numberOfRepublicanMembers
chosen
Indicates the quantity of members in a group or body who are affiliated with or belong to the Republican Party.
-
B.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
-
C.
numberOfStatesCarriedByRepublicanNominee
Indicates the number of U.S. states won or carried by the Republican presidential nominee in an election.
-
D.
republicanParty
Indicates that an entity is affiliated with, belongs to, or is a member/supporter of the Republican Party.
-
E.
RepublicanLeaderSeat
Indicates that an individual holds the leadership position for the Republican Party in a specific legislative seat or chamber.
- 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_69f6957aee008190a04d15daf49d5f08 |
completed | May 3, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69f690f13d7481908ddfefe95df2a1c2 |
completed | May 3, 2026, 12:04 a.m. |
Created at: April 29, 2026, 9:01 p.m.