Triple

T20281338
Position Surface form Disambiguated ID Type / Status
Subject Ed Corney E503150 entity
Predicate givenName P17 FINISHED
Object Ed 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: Ed | Statement: [Ed Corney, givenName, Ed]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ed
Context triple: [Ed Corney, givenName, 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 small locality in western Sweden that serves as the administrative center of Dals-Ed Municipality in Västra Götaland County.
  • C. Ed
    Ed is an American television comedy-drama series that follows a lawyer who returns to his hometown to run a bowling alley while practicing law.
  • D. 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.
  • E. ED
    ED is the standard abbreviation for the Eredivisie, the top professional football league in the Netherlands.
  • 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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6768e9f0881909c8fe8772dafd468 completed April 20, 2026, 6:55 p.m.
Created at: April 16, 2026, 10:38 a.m.