Triple

T16641423
Position Surface form Disambiguated ID Type / Status
Subject Tyler Ulis E404346 entity
Predicate givenName P17 FINISHED
Object Tyler E674057 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: Tyler | Statement: [Tyler Ulis, givenName, Tyler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tyler
Context triple: [Tyler Ulis, givenName, Tyler]
  • A. Tyler
    Tyler is a surname most prominently associated with American actress Liv Tyler and various other notable figures in entertainment and public life.
  • B. Tyler
    Tyler is a character in the 2015 horror-thriller film "The Visit," serving as one of the two grandchildren whose unsettling stay with their grandparents drives the movie’s plot.
  • C. Tyler
    Tyler is a fictional character appearing in the American television series "Kristin."
  • D. Tyler chosen
    Tyler is a masculine given name commonly used in English-speaking countries, originally derived from an occupational surname meaning "tile maker" or "house builder."
  • E. Tyler
    Tyler is a mid-sized city in East Texas known for its rose cultivation, annual Texas Rose Festival, and role as a regional medical and educational hub.
  • 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_69d8838a41f08190b0c3f79c47df5078 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ad1a7748190aa9308d4e96c566c completed April 18, 2026, 12:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0084bb4cec819091d9b7b2a09248ee completed May 10, 2026, 1:14 p.m.
Created at: April 10, 2026, 5:18 a.m.