Triple

T1441190
Position Surface form Disambiguated ID Type / Status
Subject Diana Taurasi E31075 entity
Predicate givenName P17 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: [Diana Taurasi, givenName, Diana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diana
Context triple: [Diana Taurasi, givenName, 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. Diane
    Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
  • C. Anastasia
    Anastasia is a 1956 historical drama film starring Ingrid Bergman as an amnesiac woman who may be the surviving daughter of Russia’s last tsar.
  • D. Rachel
    Rachel is a prominent biblical matriarch in the Book of Genesis, known as Jacob’s beloved wife and the mother of Joseph and Benjamin.
  • E. Irene
    Irene is a feminine given name of Greek origin meaning "peace," borne by numerous historical, religious, and contemporary figures worldwide.
  • 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_69a4991633388190a4d61b5a98aa407a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c5307e988190b392f1f1d1ac10f0 completed March 1, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad0e6e12748190baeb91ba843a716f completed March 8, 2026, 5:51 a.m.
Created at: March 1, 2026, 8 p.m.