Triple
T38308776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philippine general elections |
E1033627
|
entity |
| Predicate | senateSeatsContestedEachElection |
P11588
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Philippine general elections, senateSeatsContestedEachElection, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: senateSeatsContestedEachElection Context triple: [Philippine general elections, senateSeatsContestedEachElection, 12]
-
A.
portionOfSenateContested
Indicates the fraction of seats in a senate that are up for election or otherwise being contested during a given electoral cycle.
-
B.
numberOfSeatsContested
chosen
Indicates the total count of seats in an election or contest that are being competed for or are up for selection.
-
C.
numberOfSpecialSeatsContested
Indicates the total count of special or reserved seats that are being contested in an election or selection process.
-
D.
numberOfIncumbents
Indicates the count of entities currently holding a particular position, role, or status at a given time.
-
E.
numberOfRepublicanContests
Indicates the total count of contests or events associated with the Republican Party in which an entity participated or that are attributed to it.
- 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_69f76e132c408190969b3d35c04b87ae |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fcd1499e2c81909bafd84dc4810f45 |
completed | May 7, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69fcccf024ec819086383ffbb6cfc036 |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 3, 2026, 4:30 p.m.