Triple

T13388784
Position Surface form Disambiguated ID Type / Status
Subject Toni Krinner E319515 entity
Predicate playedFor P2170 FINISHED
Object ESV Kaufbeuren E257201 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: ESV Kaufbeuren | Statement: [Toni Krinner, playedFor, ESV Kaufbeuren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ESV Kaufbeuren
Context triple: [Toni Krinner, playedFor, ESV Kaufbeuren]
  • A. ESV Kaufbeuren chosen
    ESV Kaufbeuren is a professional ice hockey club based in Kaufbeuren, Germany, competing in the German league system and known for developing notable players such as Oleg Znarok.
  • B. Neusser EV
    Neusser EV is an ice hockey club based in Neuss, Germany, competing in the lower tiers of the German ice hockey league system.
  • C. HdM Stuttgart
    HdM Stuttgart is a German university of applied sciences in Stuttgart specializing in media, communication, information, and digital technologies.
  • D. Frankfurt U3
    Frankfurt U3 is a line of the Frankfurt U-Bahn rapid transit system in Frankfurt am Main, Germany.
  • E. ESC Wedemark
    ESC Wedemark was a German ice hockey club that later became known as the Hannover Scorpions.
  • 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_69d806b886bc8190b676e7768b8e01c5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dba0d3a40081909ba49556130ad0e7 completed April 12, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f72691c8d08190b971d7e914863cc1 completed May 3, 2026, 10:42 a.m.
Created at: April 9, 2026, 9:34 p.m.