Triple

T21709012
Position Surface form Disambiguated ID Type / Status
Subject Sara Paxton E535849 entity
Predicate performedIn P795 FINISHED
Object Liar Liar Vampire NE NERFINISHED

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: Liar Liar Vampire | Statement: [Sara Paxton, performedIn, Liar Liar Vampire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liar Liar Vampire
Context triple: [Sara Paxton, performedIn, Liar Liar Vampire]
  • A. Liar Liar Vampire chosen
    Liar Liar Vampire is a 2015 Nickelodeon teen comedy film about a high school boy who pretends to be a vampire to gain popularity.
  • B. The Last American Vampire
    The Last American Vampire is a supernatural historical novel by Seth Grahame-Smith that follows the immortal vampire Henry Sturges as he navigates key events in American history.
  • C. Mr. Vampire
    Mr. Vampire is a classic 1985 Hong Kong horror-comedy film that popularized the hopping vampire (jiangshi) genre and became a landmark of Chinese supernatural cinema.
  • D. Vampirina
    Vampirina is an animated Disney Junior television series that follows a young vampire girl adjusting to life in the human world after moving from Transylvania to Pennsylvania.
  • E. Lust for a Vampire
    Lust for a Vampire is a 1971 British Hammer horror film about a resurrected female vampire preying on students at an all-girls finishing school.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c46b44c0819088ab883ebd44e0e8 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69efb5321d34819091f3cd03f7b407c0 completed April 27, 2026, 7:12 p.m.
Created at: April 16, 2026, 6:46 p.m.