Triple

T7299730
Position Surface form Disambiguated ID Type / Status
Subject Gospel of John E167813 entity
Predicate keyChristologicalTitle P33442 FINISHED
Object Logos E19415 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: Logos | Statement: [Gospel of John, keyChristologicalTitle, Logos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Logos
Context triple: [Gospel of John, keyChristologicalTitle, Logos]
  • A. Logos chosen
    Logos is a central concept in Christian theology referring to the divine Word or reason of God, identified with Christ as the preexistent and incarnate Son.
  • B. The Logo
    The Logo is the famous nickname of NBA legend Jerry West, referencing his iconic silhouette used in the league’s official logo.
  • C. Monogram
    Monogram is a famous mixed-media artwork by Robert Rauschenberg featuring a taxidermied goat encircled by a tire, emblematic of his groundbreaking “combine” paintings that merge painting and sculpture.
  • D. Loggos
    Loggos is a small, picturesque coastal village on the Greek island of Paxos, known for its harbor, traditional tavernas, and relaxed atmosphere.
  • E. Logo
    Logo is an educational programming language known for its turtle graphics, designed to help learners explore mathematical and computational ideas through simple commands.
  • 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_69c6888c820881909fc68f689fe1c251 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6ebad1b4481909e49ccc580007e4b completed March 27, 2026, 8:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7e550645c819085effd46dff60f09 completed March 28, 2026, 2:27 p.m.
Created at: March 27, 2026, 3:01 p.m.