Triple

T6238646
Position Surface form Disambiguated ID Type / Status
Subject Ray Stevens E139538 entity
Predicate notableSong P4 FINISHED
Object Ahab the Arab E577587 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: Ahab the Arab | Statement: [Ray Stevens, notableSong, Ahab the Arab]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ahab the Arab
Context triple: [Ray Stevens, notableSong, Ahab the Arab]
  • A. Ahab the Arab chosen
    Ahab the Arab is a 1962 novelty song by American singer-comedian Ray Stevens that humorously tells the story of a cartoonish Middle Eastern character.
  • B. Aaron the Moor
    Aaron the Moor is a cunning and villainous character in Shakespeare's tragedy "Titus Andronicus," known for his manipulative cruelty and outsider status as a Black man in Roman society.
  • C. Ishmael Boorg
    Ishmael Boorg is a fictional character known for serving as a powerful crime lord and central antagonist in his narrative universe.
  • D. Shimr ibn Dhi’l-Jawshan
    Shimr ibn Dhi’l-Jawshan was an Umayyad military figure infamous in Islamic history for his leading role in the killing of Husayn ibn Ali at Karbala.
  • E. Mr. Arabin
    Mr. Arabin is a clergyman and academic who becomes a central romantic interest in Anthony Trollope’s novel "Barchester Towers."
  • 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_69c008b0e7ac8190808a59573ee646f3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063048df081909a13d16b6f6bf65d completed March 22, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c243ff29248190abbb748601039f60 completed March 24, 2026, 7:57 a.m.
Created at: March 22, 2026, 4:23 p.m.