Triple
T9644631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilma Pang |
E233162
|
entity |
| Predicate | typeOfElectionContested |
P89413
|
FINISHED |
| Object | municipal election |
—
|
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: municipal election | Statement: [Wilma Pang, typeOfElectionContested, municipal election]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfElectionContested Context triple: [Wilma Pang, typeOfElectionContested, municipal election]
-
A.
numberOfSeatsContested
Indicates the total count of seats in an election or contest that are being competed for or are up for selection.
-
B.
electionContests
Indicates that one election is in competition with, or formally challenges the outcome or validity of, another election.
-
C.
electionNumber
Indicates the specific ordinal or identifying number assigned to a particular election within a series or system of elections.
-
D.
electionHeldIn
Indicates that an election event took place within a specific geographic or political location.
-
E.
electoralDistrictType
Indicates the specific category or kind of electoral district associated with an entity (e.g., federal, state, local).
- F. None of above. chosen
Provenance (4 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_69ca848a5a908190aad251f4137b0c3a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b7fd2308190803a196ecdc80d76 |
completed | April 1, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b0263081908cf6df3eb07d71b0 |
completed | April 1, 2026, 8:22 a.m. |
| PDg | Predicate description generation | batch_69ccd9408c848190b84dd74d87f76273 |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:12 p.m.