Triple

T5417731
Position Surface form Disambiguated ID Type / Status
Subject Entertaining Mr Sloane E121171 entity
Predicate featuresCharacter P626 FINISHED
Object Ed E3080 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: Ed | Statement: [Entertaining Mr Sloane, featuresCharacter, Ed]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ed
Context triple: [Entertaining Mr Sloane, featuresCharacter, Ed]
  • A. Ed chosen
    Ed is a common masculine given name, typically used as a short form of names such as Edward, Edwin, or Edmund.
  • B. ED
    ED is a classic line-based text editor commonly used in Unix-like operating systems, known for its minimal interface and suitability for scripting and low-resource environments.
  • C. ED
    ED is the federal agency responsible for establishing policy, administering, and coordinating most education-related programs in the United States.
  • D. EB
    EB is the Executive Board of the World Health Organization, a governing body that advises and facilitates the implementation of the World Health Assembly’s decisions and policies.
  • E. EB
    EB is the regional vehicle registration code used on license plates for vehicles registered in Alexandroupoli, Greece.
  • 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_69bd463a41cc8190b32ff5af2b96ca93 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd87e620f081909eb9a5e1f284e5a2 completed March 20, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf3aadfa4c81908b57af80f534b121 completed March 22, 2026, 12:41 a.m.
Created at: March 20, 2026, 2:05 p.m.