Triple

T17170833
Position Surface form Disambiguated ID Type / Status
Subject Amy Spanger E416726 entity
Predicate notableWork P4 FINISHED
Object Ed E910176 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: [Amy Spanger, notableWork, Ed]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ed
Context triple: [Amy Spanger, notableWork, Ed]
  • A. Ed
    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 chosen
    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 (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_69d886d5f34c8190b24564dfaa63f3fb completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3fc097950819095631ee5679e03af completed April 18, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01483f85648190acaeb197013e1f1b completed May 11, 2026, 3:08 a.m.
Created at: April 10, 2026, 5:37 a.m.