Triple

T25761247
Position Surface form Disambiguated ID Type / Status
Subject U.S. Senate seats from California E648743 entity
Predicate contrastWithHouse P123206 FINISHED
Object not based on population 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: not based on population | Statement: [U.S. Senate seats from California, contrastWithHouse, not based on population]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: contrastWithHouse
Context triple: [U.S. Senate seats from California, contrastWithHouse, not based on population]
  • A. contrastUse
    Indicates that one entity is used in opposition or distinction to another to highlight differences between them.
  • B. contrastEnvironment
    Indicates a relationship where one environment is compared against another to highlight their differences or opposing characteristics.
  • C. providesContrastWith chosen
    Indicates that one entity is used to highlight differences or distinctions when compared with another entity.
  • D. dramaticContrastWith
    Indicates that one entity is presented in a way that sharply emphasizes differences in tone, style, or impact when compared with another entity.
  • E. contrastGoal
    Indicates a relationship where one goal is defined in opposition to, or as a contrasting alternative to, another goal.
  • 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_69e7ab322db0819092d6a2b3d4572e01 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f6691f5e188190b12c7b2eb729a45e completed May 2, 2026, 9:14 p.m.
PD Predicate disambiguation batch_69f66598d6008190a7ca8ff80399fd34 completed May 2, 2026, 8:59 p.m.
Created at: April 22, 2026, 5:05 a.m.