Triple

T22027376
Position Surface form Disambiguated ID Type / Status
Subject RFC 3489 E544001 entity
Predicate author P4 FINISHED
Object Christian Huitema 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: Christian Huitema | Statement: [RFC 3489, author, Christian Huitema]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christian Huitema
Context triple: [RFC 3489, author, Christian Huitema]
  • A. Christian Huitema chosen
    Christian Huitema is a French computer scientist and Internet pioneer known for his influential work on networking protocols and IPv6 transition technologies.
  • B. Johan Hoogewijs
    Johan Hoogewijs is a Belgian composer best known for his film and television scores.
  • C. George Verschoor
    George Verschoor is a television producer and director best known for pioneering and executive producing influential reality and documentary-style series.
  • D. Sander van Doorn
    Sander van Doorn is a Dutch DJ and electronic music producer known for his influential work in trance and progressive house.
  • E. Dennis van Aarssen
    Dennis van Aarssen is a Dutch jazz and pop singer who gained national fame after winning the talent show The Voice of Holland.
  • 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_69e11e2e8ea4819084210fe06d3a1b8d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127ccc2ec8190a94d69530d00c06c completed April 28, 2026, 9:34 p.m.
Created at: April 16, 2026, 8:24 p.m.