Triple

T20385761
Position Surface form Disambiguated ID Type / Status
Subject Amanda Grayson E497951 entity
Predicate child P120 FINISHED
Object Sybok NE NERFINISHED

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: Sybok | Statement: [Amanda Grayson, child, Sybok]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sybok
Context triple: [Amanda Grayson, child, Sybok]
  • A. Sybok chosen
    Sybok is a Vulcan character in the Star Trek universe known for rejecting traditional Vulcan logic in favor of embracing and exploring emotions.
  • B. Nikto
    Nikto is an open-source web server vulnerability scanner that tests for dangerous files, outdated server software, and other common security issues.
  • C. Shagbat
    Shagbat is an informal nickname for the Supermarine Walrus, a British World War II-era amphibious reconnaissance and air-sea rescue aircraft.
  • D. Shinzon
    Shinzon is a human clone of Captain Jean-Luc Picard who leads a coup against the Romulan government and serves as the primary villain in the film Star Trek: Nemesis.
  • E. Nokk
    Nokk is a mythical water spirit from Scandinavian folklore, often depicted as a shape-shifting creature that lures people into lakes and rivers.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4a71ebc8190b153a36c738730f4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6790bcef481909453d19c846ab420 completed April 20, 2026, 7:05 p.m.
Created at: April 16, 2026, 11:28 a.m.