Triple

T16618989
Position Surface form Disambiguated ID Type / Status
Subject Shailene Woodley E403769 entity
Predicate birthName P65 FINISHED
Object Shailene Diann Woodley E403769 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: Shailene Diann Woodley | Statement: [Shailene Woodley, birthName, Shailene Diann Woodley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shailene Diann Woodley
Context triple: [Shailene Woodley, birthName, Shailene Diann Woodley]
  • A. Shailene Woodley chosen
    Shailene Woodley is an American actress known for her breakout role in "The Descendants" and for starring in films such as "The Fault in Our Stars" and the "Divergent" series.
  • B. Julia Fox
    Julia Fox is an Italian-American actress and artist best known for her breakout role in the Safdie brothers’ crime thriller "Uncut Gems."
  • C. Emma Stone
    Emma Stone is an American actress acclaimed for her versatile performances in films such as "La La Land," for which she won the Academy Award for Best Actress.
  • D. Juno Temple
    Juno Temple is an English actress known for her eclectic film roles and acclaimed performance as Keeley Jones in the television series "Ted Lasso."
  • E. Angourie Rice
    Angourie Rice is an Australian actress known for her breakout role in "The Nice Guys" and for appearing in films such as "Spider-Man: Homecoming" and "Spider-Man: Far From Home."
  • 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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3754c934c8190a0a8ddd747681aa7 completed April 18, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0084b5afc081908d16f0b43fff20fc completed May 10, 2026, 1:14 p.m.
Created at: April 10, 2026, 5:17 a.m.