Triple

T16894096
Position Surface form Disambiguated ID Type / Status
Subject Eliza Scanlen E424252 entity
Predicate work P12692 FINISHED
Object Babyteeth E1239960 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: Babyteeth | Statement: [Eliza Scanlen, work, Babyteeth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Babyteeth
Context triple: [Eliza Scanlen, work, Babyteeth]
  • A. Babyteeth chosen
    Babyteeth is a 2019 Australian coming-of-age drama film about a gravely ill teenage girl who falls in love with a small-time drug dealer, adapted from Rita Kalnejais's stage play of the same name.
  • B. Night Teeth
    Night Teeth is a 2021 Netflix horror-thriller film about a college student who becomes entangled with vampires during a night of chauffeuring mysterious women around Los Angeles.
  • C. White Tooth
    White Tooth is the English meaning of the name "Dent Blanche," a prominent mountain in the Pennine Alps of Switzerland.
  • D. The Tooth
    "The Tooth" is a short story by Shirley Jackson, included in her collection *The Lottery and Other Stories*, that blends psychological unease with elements of the uncanny.
  • E. Sweet Tooth
    Sweet Tooth is a 2012 espionage novel by Ian McEwan that blends Cold War spy intrigue with a metafictional love story set in 1970s Britain.
  • 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_69d889da3e8c8190a2b118f383f0beac completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3c8d6bfc88190b6b47b89c1135871 completed April 18, 2026, 6:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00cfca11bc8190b0835de0d56ca0b1 completed May 10, 2026, 6:34 p.m.
Created at: April 10, 2026, 5:29 a.m.