Triple

T12481507
Position Surface form Disambiguated ID Type / Status
Subject Tekno E298317 entity
Predicate notableWork P4 FINISHED
Object Diana E71669 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: Diana | Statement: [Tekno, notableWork, Diana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diana
Context triple: [Tekno, notableWork, Diana]
  • A. Diana chosen
    Diana is a feminine given name of Latin origin, famously borne by the Roman goddess of the hunt and by Diana, Princess of Wales.
  • B. Diana
    Diana is a renowned sculpture by Brazilian-Italian modernist artist Victor Brecheret, exemplifying his stylized, classical approach to the human figure.
  • C. Melina
    Melina is a key resistance fighter and love interest in the science fiction film "Total Recall," known for aiding the protagonist in his struggle against a corrupt Martian regime.
  • D. Roxanna
    Roxanna is a feminine given name of Persian origin, commonly interpreted to mean "dawn" or "bright."
  • E. Diane
    Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94dcef6548190a6d29375bdabd17d completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f29307c8190b024d889d45ba9f7 completed May 2, 2026, 6:15 p.m.
Created at: April 8, 2026, 9:56 p.m.