Triple

T20385119
Position Surface form Disambiguated ID Type / Status
Subject Almost Angels E497938 entity
Predicate castMember P1668 FINISHED
Object Hans Holt 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: Hans Holt | Statement: [Almost Angels, castMember, Hans Holt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hans Holt
Context triple: [Almost Angels, castMember, Hans Holt]
  • A. Hans Holt chosen
    Hans Holt was an Austrian actor known for his roles in mid-20th-century German-language cinema and international productions.
  • B. Hans Hansen
    Hans Hansen is a central character in Thomas Mann's novella "Tonio Kröger," representing the idealized, conventional bourgeois youth who contrasts with the artistic, introspective protagonist.
  • C. Thomas Heggen
    Thomas Heggen was an American author best known for his World War II–era novel "Mister Roberts," which became a hugely successful play and film.
  • D. George Hansen
    George Hansen is a fictional character from the 1958 Western film "Terror in a Texas Town."
  • E. George Hansen
    George Hansen is a relatively common personal name that may refer to multiple individuals across different fields, such as politics, sports, or academia.
  • 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_69e0b4a71ebc8190b153a36c738730f4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6790a31a4819099b2e6df2bafe547 completed April 20, 2026, 7:05 p.m.
Created at: April 16, 2026, 11:28 a.m.