Triple

T1910212
Position Surface form Disambiguated ID Type / Status
Subject Michael Ian Black E38090 entity
Predicate knownFor P22 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: [Michael Ian Black, knownFor, Ed]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ed
Context triple: [Michael Ian Black, knownFor, 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. Em
    Em is a common shortened form of the given name Emma, often used as an informal nickname.
  • 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_69a8862a26088190aae5243695aeefc0 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb1b7095c8190ad7e472aada30d3d completed March 7, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeaffbc2c81908303548fac82ff52 completed March 8, 2026, 9:32 p.m.
Created at: March 4, 2026, 7:35 p.m.