Triple

T3735549
Position Surface form Disambiguated ID Type / Status
Subject Klaus Heissler E79173 entity
Predicate givenName P17 FINISHED
Object Klaus E103973 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: Klaus | Statement: [Klaus Heissler, givenName, Klaus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Klaus
Context triple: [Klaus Heissler, givenName, Klaus]
  • A. Klaus chosen
    Klaus is a masculine given name of German origin commonly used in German-speaking countries.
  • B. Krampus
    Krampus is a horned, demonic figure from Central European folklore who punishes misbehaving children during the Christmas season, often appearing alongside Saint Nicholas.
  • C. Krampus (2015 film)
    Krampus (2015 film) is a 2015 horror-comedy movie that blends dark folklore and holiday themes, following a dysfunctional family terrorized by the demonic Christmas figure Krampus.
  • D. Isles of Wonder
    Isles of Wonder was the theatrical, cinematic-themed opening ceremony of the London 2012 Olympic Games, directed by Danny Boyle and celebrating British history and culture.
  • E. Grimm
    Grimm is a dark fantasy police procedural television series that blends crime-solving with folklore-inspired supernatural elements.
  • 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_69ad8b0e4650819090ad7cef094285e8 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb3b399c819091b42209925c0d8f completed March 8, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db1be1388190a887d9eca0f4f9b3 completed March 14, 2026, 3:50 a.m.
Created at: March 8, 2026, 3:34 p.m.