Triple
T4385569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pennsylvania's 11th congressional district |
E99232
|
entity |
| Predicate | hasElectionMonth |
P48165
|
FINISHED |
| Object | November |
—
|
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: November | Statement: [Pennsylvania's 11th congressional district, hasElectionMonth, November]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasElectionMonth Context triple: [Pennsylvania's 11th congressional district, hasElectionMonth, November]
-
A.
hasElection
Indicates that an entity conducts, holds, or is associated with an election event.
-
B.
hasElectionsFor
Indicates that a governing body, jurisdiction, or organization conducts elections to select or appoint members to a specified office, role, or representative body.
-
C.
generalElectionMonth
chosen
Indicates the month during which a general election is scheduled to occur or took place.
-
D.
hasByElections
Indicates that one entity conducts, experiences, or is associated with one or more by-elections in relation to another contextual entity (such as a jurisdiction, office, or time period).
-
E.
hasElectionType
Indicates the specific category or kind of election associated with a given electoral event or process.
- 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_69b3454f739481909ff6c28331f0c0b9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35264e44c81908dd0e0a81f1353bb |
completed | March 12, 2026, 11:55 p.m. |
| PD | Predicate disambiguation | batch_69b34f572efc8190bad1e5078cbcb75a |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:19 p.m.