Triple

T12641258
Position Surface form Disambiguated ID Type / Status
Subject Tanis E301902 entity
Predicate majorDeityWorshipped P7648 FINISHED
Object Set E56545 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: Set | Statement: [Tanis, majorDeityWorshipped, Set]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Set
Context triple: [Tanis, majorDeityWorshipped, Set]
  • A. Set chosen
    Set is an ancient Egyptian god associated primarily with chaos, storms, and disorder, often depicted as the adversary of his brother Osiris and the rival of Horus.
  • B. SETS
    SETS is the London Stock Exchange’s central electronic order book system used for automated trading of the most liquid UK securities.
  • C. SET
    SET is an open-source penetration testing framework focused on social engineering attacks, commonly used by security professionals to simulate and assess human-targeted vulnerabilities.
  • D. SET
    SET is the Stock Exchange of Thailand, the primary securities exchange for trading stocks and other financial instruments in Thailand.
  • E. NSSet
    NSSet is an Objective-C collection class that represents an unordered, unique set of objects, commonly used in Cocoa and Cocoa Touch frameworks.
  • 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_69d7bdec9f9c8190b4bac675b7588211 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9614ae6ac8190b42acbf2b0331fda completed April 10, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6687770388190b4777885dae8a38f completed May 2, 2026, 9:11 p.m.
Created at: April 9, 2026, 5:17 p.m.