Triple

T6514878
Position Surface form Disambiguated ID Type / Status
Subject The Jewish Barber E148229 entity
Predicate hasAlly P600 FINISHED
Object Hannah E162501 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: Hannah | Statement: [The Jewish Barber, hasAlly, Hannah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hannah
Context triple: [The Jewish Barber, hasAlly, Hannah]
  • A. Hannah
    Hannah is a biblical figure in the Book of 1 Samuel known for her fervent prayer for a child and as the mother of the prophet Samuel.
  • B. Hannah
    Hannah is a person associated in some way with the city of Santa Ana, California.
  • C. Hannah chosen
    Hannah is a compassionate Jewish laundress and the love interest of the Jewish Barber in Charlie Chaplin’s 1940 satirical film "The Great Dictator."
  • D. Hannah
    Hannah is a key survivor character in the British post-apocalyptic horror film "28 Days Later," known for her resilience and resourcefulness amid a rage virus outbreak in London.
  • E. Hannah
    Hannah is an alternate given name associated with American actress Dakota Fanning, whose full name is Hannah Dakota Fanning.
  • 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_69c687e68e748190baceb9298f32d3ed completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6ac0bea808190aebc2905fb53eeba completed March 27, 2026, 4:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d5125c448190bf47843fcac66efe completed March 27, 2026, 7:05 p.m.
Created at: March 27, 2026, 1:44 p.m.