Triple

T18841689
Position Surface form Disambiguated ID Type / Status
Subject Zuckerhütl E460812 entity
Predicate parentPeak P1319 FINISHED
Object Wilder Freiger 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: Wilder Freiger | Statement: [Zuckerhütl, parentPeak, Wilder Freiger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wilder Freiger
Context triple: [Zuckerhütl, parentPeak, Wilder Freiger]
  • A. Wilder Freiger chosen
    Wilder Freiger is a prominent mountain peak in the Central Eastern Alps, straddling the border between Austria and Italy and popular with climbers for its glaciated terrain and panoramic views.
  • B. Frank Grau
    Frank Grau is a musician best known as a former member of the experimental rock band Sleepytime Gorilla Museum.
  • C. Anthony Kilhoffer
    Anthony Kilhoffer is a Grammy-winning American record producer and audio engineer known for his extensive work with artists like Kanye West and other major hip-hop and pop acts.
  • D. William Wiegand
    William Wiegand was an American writer and critic known for his contributions to mid-20th-century literary culture.
  • E. Henry Freulich
    Henry Freulich was an American cinematographer known for his extensive work on Hollywood films from the 1930s through the 1950s, particularly at Columbia Pictures.
  • 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_69d8dcfa11e4819090ab1ef5bdcd2b2e completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5b8ea35c88190af6659551ad18130 completed April 20, 2026, 5:26 a.m.
Created at: April 10, 2026, 11:56 a.m.