Triple

T15672227
Position Surface form Disambiguated ID Type / Status
Subject Orthrus E377342 entity
Predicate sibling P363 FINISHED
Object Sphinx E111286 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: Sphinx | Statement: [Orthrus, sibling, Sphinx]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sphinx
Context triple: [Orthrus, sibling, Sphinx]
  • A. Sphinx chosen
    The Sphinx is a mythical creature, typically depicted with a lion's body and a human head, known for posing deadly riddles to travelers in Greek mythology.
  • B. Sphinx
    Sphinx is a documentation generation tool that converts reStructuredText (and other formats) into HTML, PDF, and other outputs, widely used for Python projects and technical documentation.
  • C. Sphinx
    Sphinx is a taciturn, highly skilled mechanic and member of the car-stealing crew in the film "Gone in 60 Seconds."
  • D. Sphinx of Naxos
    The Sphinx of Naxos is an ancient Greek monumental statue of a winged female sphinx dedicated by the island of Naxos at Delphi, renowned for its Archaic style and imposing scale.
  • E. The Sphinx
    The Sphinx is the official magazine of Alpha Phi Alpha Fraternity, Inc., serving as a historical record and communication organ for its members.
  • 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f13b1b08190beabc9f4098aa096 completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ed8d9188190a68035d2508b117d completed May 9, 2026, 5:28 p.m.
Created at: April 10, 2026, 4:16 a.m.