Triple

T14982364
Position Surface form Disambiguated ID Type / Status
Subject Steve Freeling E373608 entity
Predicate protects P1040 FINISHED
Object Dana Freeling E1229026 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: Dana Freeling | Statement: [Steve Freeling, protects, Dana Freeling]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dana Freeling
Context triple: [Steve Freeling, protects, Dana Freeling]
  • A. Dana Freeling chosen
    Dana Freeling is a fictional character from the "Poltergeist" horror film series, known as the eldest daughter in the Freeling family.
  • B. Carol Anne Freeling
    Carol Anne Freeling is the young girl at the center of the supernatural events in the Poltergeist film series, known for being abducted by malevolent spirits through her family's television.
  • C. Dawn Freeman
    Dawn Freeman is known as the wife of late American heavyweight boxer and former WBO champion Tommy Morrison.
  • D. Dana Congdon
    Dana Congdon is a film editor best known for his work on movies such as the anthology comedy "Four Rooms."
  • E. Diane Coulston
    Diane Coulston is a teenage schoolgirl in the film "T2 Trainspotting," known for her past relationship with protagonist Mark Renton and her sharp, grounded perspective on the aging former heroin users.
  • 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_69d85ccbbcd48190acb56e7cf104d8ad completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6fe42a081909308f788fdf024d5 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00aade82788190a5f3cedbc22065c4 completed May 10, 2026, 3:57 p.m.
Created at: April 10, 2026, 2:52 a.m.