Triple

T5742690
Position Surface form Disambiguated ID Type / Status
Subject Paula Hawkins E126652 entity
Predicate wrote P2831 FINISHED
Object Into the Water E545947 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: Into the Water | Statement: [Paula Hawkins, wrote, Into the Water]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Into the Water
Context triple: [Paula Hawkins, wrote, Into the Water]
  • A. Into the Water chosen
    Into the Water is a psychological thriller novel by Paula Hawkins that explores memory, trauma, and the dark secrets of a small English town surrounding a series of mysterious drownings.
  • B. Into the Ocean
    "Into the Ocean" is a melancholic alternative rock song by Blue October that blends introspective lyrics about loss and depression with a haunting, melodic arrangement.
  • C. Beneath Still Waters
    "Beneath Still Waters" is a country song popularized by Emmylou Harris, known for its haunting melody and emotionally resonant lyrics about hidden heartache.
  • D. What the Water Gave Me
    "What the Water Gave Me" is an ethereal, art-rock-influenced song by English band Florence and the Machine, known for its sweeping vocals, literary references, and richly layered production.
  • E. Dark Water
    Dark Water is a 2005 American supernatural horror film, adapted from a Japanese story, about a mother and daughter haunted by mysterious water-related phenomena in their new apartment.
  • 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_69c0083179548190b384b0bf3c08ca4d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c025852a2c819080521e5b98c00bdc completed March 22, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c097f9b6e08190bb68ea850ba813ff completed March 23, 2026, 1:31 a.m.
Created at: March 22, 2026, 3:48 p.m.