Triple

T4416981
Position Surface form Disambiguated ID Type / Status
Subject Tennessee General Assembly E94997 entity
Predicate apportions P1682 FINISHED
Object legislative districts in Tennessee 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: legislative districts in Tennessee | Statement: [Tennessee General Assembly, apportions, legislative districts in Tennessee]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: apportions
Context triple: [Tennessee General Assembly, apportions, legislative districts in Tennessee]
  • A. apportionedBy chosen
    Indicates that something is divided or allocated among parts or recipients according to a specified agent, rule, or method.
  • B. apportionedAfter
    Indicates that one entity is distributed, allocated, or divided only after another specified event, action, or allocation has occurred.
  • C. apportionmentUnit
    Indicates a relationship where something (such as a resource, cost, or quantity) is divided or allocated according to a specified unit or basis of apportionment.
  • D. elects
    Indicates that one entity selects or chooses another entity for a position, role, or office, typically through a formal voting process.
  • E. fractionAppointed
    Indicates the proportion of positions or roles within a group or organization that have been formally filled or assigned.
  • 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_69b3453a36908190b95a79a297ca083c completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3551afb448190a2ce2000193808ac completed March 13, 2026, 12:06 a.m.
PD Predicate disambiguation batch_69b34f5d0c54819085c08533bb58030a completed March 12, 2026, 11:42 p.m.
Created at: March 12, 2026, 11:29 p.m.