Triple

T19327155
Position Surface form Disambiguated ID Type / Status
Subject The Tree E483389 entity
Predicate title P38 FINISHED
Object The Tree 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: The Tree | Statement: [The Tree, title, The Tree]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Tree
Context triple: [The Tree, title, The Tree]
  • A. The Tree chosen
    "The Tree" is a minimalist abstract painting by American artist Agnes Martin, exemplifying her serene grid-based style and meditative approach to art.
  • B. The Wood
    The Wood is the nickname of Boreham Wood F.C., an English football club based in Borehamwood, Hertfordshire.
  • C. The Wood
    "The Wood" is a 1999 coming-of-age comedy-drama film that follows three lifelong friends in Inglewood, California, as they reminisce about their youth on the day of one friend's wedding.
  • D. The Forest Trees
    The Forest Trees is a short story by Washington Irving included in his 1822 collection "Bracebridge Hall; or, The Humorists."
  • E. The Three Trees
    The Three Trees is a renowned 1643 landscape etching by Rembrandt, celebrated for its dramatic chiaroscuro and atmospheric depiction of a stormy countryside.
  • 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_69d8e8d13e3c81909d91d1d5ec37c095 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e6163e3a5081909195192356bcebc3 completed April 20, 2026, 12:04 p.m.
Created at: April 10, 2026, 1:33 p.m.