Triple

T5867447
Position Surface form Disambiguated ID Type / Status
Subject Eredivisie E130430 entity
Predicate abbreviation P43 FINISHED
Object ED
ED is the standard abbreviation for the Eredivisie, the top professional football league in the Netherlands.
 E549807 NE FINISHED

How this triple was built (4 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: [Eredivisie, abbreviation, ED]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ED
Context triple: [Eredivisie, abbreviation, ED]
  • A. ED
    ED is the federal agency responsible for establishing policy, administering, and coordinating most education-related programs in the United States.
  • 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 a common masculine given name, typically used as a short form of names such as Edward, Edwin, or Edmund.
  • D. EC
    EC is the two-letter ISO 3166-1 alpha-2 country code assigned to Ecuador.
  • E. EC
    EC is the abbreviation for the APEC Economic Committee, a body that supports economic policy research and cooperation among APEC member economies.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: ED
Triple: [Eredivisie, abbreviation, ED]
Generated description
ED is the standard abbreviation for the Eredivisie, the top professional football league in the Netherlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ED
Target entity description: ED is the standard abbreviation for the Eredivisie, the top professional football league in the Netherlands.
  • A. ED
    ED is the federal agency responsible for establishing policy, administering, and coordinating most education-related programs in the United States.
  • 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 a common masculine given name, typically used as a short form of names such as Edward, Edwin, or Edmund.
  • D. EC
    EC is the two-letter ISO 3166-1 alpha-2 country code assigned to Ecuador.
  • E. EC
    EC is a central London postcode area covering much of the historic City of London and parts of the surrounding financial district.
  • F. None of above. chosen

Provenance (5 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_69c0085047dc8190af24e311edad3c07 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c035c27e708190b46c707d61c78877 completed March 22, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a1d0c5a88190be8dee862e71a0f6 completed March 23, 2026, 2:13 a.m.
NEDg Description generation batch_69c0a2ab17f481908f2d492e4d9d90fb completed March 23, 2026, 2:17 a.m.
NED2 Entity disambiguation (via description) batch_69c0a325410c8190925e5d9961baf829 completed March 23, 2026, 2:19 a.m.
Created at: March 22, 2026, 3:56 p.m.