Triple

T20001030
Position Surface form Disambiguated ID Type / Status
Subject great white shark (Jaws) E494325 entity
Predicate kills P19780 FINISHED
Object Chrissie Watkins 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: Chrissie Watkins | Statement: [great white shark (Jaws), kills, Chrissie Watkins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chrissie Watkins
Context triple: [great white shark (Jaws), kills, Chrissie Watkins]
  • A. Chrissie Watkins chosen
    Chrissie Watkins is the young woman whose fatal shark attack in the opening scene of the film "Jaws" sets the story’s events in motion.
  • B. Chrissie Williams
    Chrissie Williams is a fictional senior nurse and ward sister from the British medical drama series "Holby City."
  • C. Chrissie Mullen
    Chrissie Mullen is best known as the first wife of Queen guitarist Brian May, with whom she was married during the early years of the band’s success.
  • D. Carlene Watkins
    Carlene Watkins is an American television actress known for her roles in various sitcoms and TV series from the late 1970s onward.
  • E. Crissy Haslam
    Crissy Haslam is an American educator and former First Lady of Tennessee, known for her advocacy on literacy and children's issues during her husband Bill Haslam's governorship.
  • 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e661a222908190b88e1d11cb1b7ee3 completed April 20, 2026, 5:25 p.m.
Created at: April 11, 2026, 3:32 p.m.