Triple

T5354818
Position Surface form Disambiguated ID Type / Status
Subject Austen Chamberlain E102664 entity
Predicate givenName P17 FINISHED
Object Joseph E77392 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: Joseph | Statement: [Austen Chamberlain, givenName, Joseph]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joseph
Context triple: [Austen Chamberlain, givenName, Joseph]
  • A. Joseph
    Joseph is the first name of J. C. R. Licklider, a pioneering computer scientist often regarded as a key figure in the development of the internet and interactive computing.
  • B. Joseph
    Joseph is the husband of Mary in the New Testament and the earthly guardian of Jesus, venerated in Christianity as a model of humility, obedience, and fatherhood.
  • C. Joseph
    Joseph is the given name of the French mathematician and physicist Jean-Baptiste Joseph Fourier, known for developing Fourier analysis and Fourier series.
  • D. Joseph chosen
    Joseph is a common masculine given name of Hebrew origin, traditionally interpreted to mean "He will add" or "God increases."
  • E. Joseph
    Joseph is the given first name of Joe Torre, the former Major League Baseball player and Hall of Fame manager best known for leading the New York Yankees to multiple World Series titles.
  • 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_69bd43d8f7248190b64c140734b5c9a8 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd862dbb008190aef653acddafd38b completed March 20, 2026, 5:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf21df856c819099cf9047b87d6db8 completed March 21, 2026, 10:55 p.m.
Created at: March 20, 2026, 2:01 p.m.