Triple

T14530380
Position Surface form Disambiguated ID Type / Status
Subject Joshua Ballinger Lippincott E340894 entity
Predicate hasNamePart P5298 FINISHED
Object Joshua E126068 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: Joshua | Statement: [Joshua Ballinger Lippincott, hasNamePart, Joshua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joshua
Context triple: [Joshua Ballinger Lippincott, hasNamePart, Joshua]
  • A. Joshua chosen
    Joshua is a masculine given name of Hebrew origin, commonly used in English-speaking countries.
  • B. Joshua
    Joshua is a book of the Hebrew Bible and Christian Old Testament that narrates the Israelite conquest and settlement of Canaan under the leadership of Joshua.
  • C. Joshua
    Joshua is a central biblical leader who succeeded Moses, led the Israelites into the Promised Land, and is the namesake of the Book of Joshua in the Hebrew Bible.
  • D. Joshua
    Joshua is a ruthless and highly skilled mercenary who serves as the primary henchman antagonist in the action film "Lethal Weapon."
  • E. Yoshua
    Yoshua is a male given name most notably borne by Yoshua Bengio, a pioneering Canadian computer scientist and deep learning researcher.
  • 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_69d822dac79c8190a84a073f3cbaced5 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dea052d01c81909c8592c351be6f35 completed April 14, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a547c408190a1a19e12aac1d5bd completed May 8, 2026, 5:53 a.m.
Created at: April 10, 2026, 1:22 a.m.