Triple

T9412469
Position Surface form Disambiguated ID Type / Status
Subject Nadežda Petrović E226736 entity
Predicate notableWork P4 FINISHED
Object Resnik E721521 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: Resnik | Statement: [Nadežda Petrović, notableWork, Resnik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Resnik
Context triple: [Nadežda Petrović, notableWork, Resnik]
  • A. Resnik
    Resnik is a surname most notably associated with Judith Resnik, the American astronaut who died in the Space Shuttle Challenger disaster.
  • B. Cochrane–Hearst
    Cochrane–Hearst is a bus route in northeastern Ontario, Canada, connecting the communities of Cochrane and Hearst.
  • C. Charikar
    Charikar is a city in northern Afghanistan that serves as the capital of Parwan Province and a key hub on the route between Kabul and the northern regions.
  • D. Reznik chosen
    Reznik is a surname of likely Eastern European origin, often associated with Jewish and Slavic families and appearing in various transliterated forms such as Resnick.
  • E. Abelson
    Abelson is a surname most notably associated with Hal Abelson, an American computer scientist and educator known for his work on the Scheme programming language and the textbook "Structure and Interpretation of Computer Programs."
  • 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_69ca843280488190bc65600e843ef9e6 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd5258f7e081908d48600409181fdb completed April 1, 2026, 5:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69d107b0f9648190894a4cd13d7e5fb5 completed April 4, 2026, 12:44 p.m.
Created at: March 30, 2026, 7:47 p.m.