Triple

T11760250
Position Surface form Disambiguated ID Type / Status
Subject The Big Wedding E279634 entity
Predicate setting P1957 FINISHED
Object Connecticut E10549 NE 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: Connecticut | Statement: [The Big Wedding, setting, Connecticut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Connecticut
Context triple: [The Big Wedding, setting, Connecticut]
  • A. Connecticut chosen
    Connecticut is a small New England state in the northeastern United States known for its colonial history, affluent suburbs, and role as a financial and educational hub.
  • B. Rhoda Island
    Rhoda Island is a Nile island in central Cairo, Egypt, known for its historic palaces, gardens, and cultural landmarks.
  • C. Vermont
    Vermont is a small, rural New England state in the northeastern United States, known for its Green Mountains, maple syrup production, and picturesque towns.
  • D. Vermont
    Vermont is a small rural town located in Dane County, Wisconsin, known for its scenic landscapes and agricultural character.
  • E. Scotland, Connecticut
    Scotland, Connecticut is a small rural town in eastern Windham County known for its historic character and quiet, agricultural landscape.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d6ab01038c819080714901502c84fc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a52386708190b744746a2db37495 completed April 10, 2026, 7:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69f48a027dec8190aea103f0974186b0 completed May 1, 2026, 11:09 a.m.
Created at: April 8, 2026, 9:41 p.m.