Triple
T37417996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018 United States Senate election in Texas |
E929768
|
entity |
| Predicate | percentageForBetoORourke |
P166215
|
FINISHED |
| Object | 48.3% |
—
|
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: 48.3% | Statement: [2018 United States Senate election in Texas, percentageForBetoORourke, 48.3%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: percentageForBetoORourke Context triple: [2018 United States Senate election in Texas, percentageForBetoORourke, 48.3%]
-
A.
percentageForTedCruz
Indicates the proportion or percentage value associated with Ted Cruz in a given context, such as votes, support, or another measurable metric.
-
B.
opponentPopularVotePercentage
chosen
Indicates the percentage of the total popular vote received by the opposing candidate or party in an election.
-
C.
percentageParty1
Indicates the proportion or share attributed to the first party in a relationship, typically expressed as a percentage of some total.
-
D.
percentageForRepublic
Indicates the percentage value that is allocated, attributed, or applicable to the entity referred to as "Republic" within a given context.
-
E.
percentageOtherMajorCandidate
Indicates the proportion of support or votes received by candidates other than the main or major candidates in a given contest or 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_69f76ebde49481908566cd96b37ccc84 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba68077788190b311e027435fcf87 |
completed | May 6, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fba34c65ac8190b298f0f00d1dcc0e |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:16 p.m.