Triple

T8341645
Position Surface form Disambiguated ID Type / Status
Subject Tedy Lacap Bruschi E195929 entity
Predicate givenName P17 FINISHED
Object Tedy E177446 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: Tedy | Statement: [Tedy Lacap Bruschi, givenName, Tedy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tedy
Context triple: [Tedy Lacap Bruschi, givenName, Tedy]
  • A. Tedy chosen
    Tedy is the given name of Tedy Bruschi, a former professional American football linebacker best known for his career with the New England Patriots.
  • B. Teda
    Teda are a Saharan ethnic group, primarily inhabiting northern Chad and surrounding regions, known for their nomadic lifestyle and Tebu language.
  • C. Tyto
    Tyto is a genus of medium-sized owls best known for including the widespread barn owl and its close relatives.
  • D. Tede
    Tede is an archaeological site in Nigeria notable for yielding significant Ife bronze and terracotta sculptures associated with the ancient Yoruba civilization.
  • E. Tále
    Tále is a popular ski resort and recreational area in the Low Tatras mountains of central Slovakia, known for its slopes, golf course, and year-round outdoor activities.
  • 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_69ca82ecbdc481908a55cad8ca062d88 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fe9efec81908e0c9ded3963bac5 completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc72bc43c81909d95c7eb6aefc403 completed April 2, 2026, 1:32 a.m.
Created at: March 30, 2026, 5:58 p.m.