Triple

T10194253
Position Surface form Disambiguated ID Type / Status
Subject Elizabethtown E238117 entity
Predicate editor P1954 FINISHED
Object David Moritz E312086 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: David Moritz | Statement: [Elizabethtown, editor, David Moritz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Moritz
Context triple: [Elizabethtown, editor, David Moritz]
  • A. David Moritz chosen
    David Moritz is a film editor known for his work on notable movies including "The Life Aquatic with Steve Zissou."
  • B. Eduard Meyer
    Eduard Meyer was a prominent German historian and classical scholar known for his influential works on ancient history and historiography.
  • C. Johann David Michaelis
    Johann David Michaelis was an 18th-century German biblical scholar and orientalist known for his influential work in Hebrew and Old Testament studies.
  • D. Henry Meybohm
    Henry Meybohm was a mountaineer known for participating in the first ascent of Mount Hunter in Alaska.
  • E. Philipp von Jolly
    Philipp von Jolly was a 19th-century German physicist and mathematician known for his work in experimental physics and for mentoring future Nobel laureate Max Planck.
  • 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_69ca84de1b208190bf17bb305b002605 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdedc7cc748190bceb8f657afcc054 completed April 2, 2026, 4:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d35512ab2c8190b2802c7bb22e7323 completed April 6, 2026, 6:39 a.m.
Created at: March 30, 2026, 9:13 p.m.