Triple

T201244
Position Surface form Disambiguated ID Type / Status
Subject United States Department of Education E4508 entity
Predicate abbreviation P43 FINISHED
Object ED
ED is the federal agency responsible for establishing policy, administering, and coordinating most education-related programs in the United States.
 E25791 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: [United States Department of Education, abbreviation, ED]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ED
Context triple: [United States Department of Education, abbreviation, 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. EC
    EC is the two-letter ISO 3166-1 alpha-2 country code assigned to Ecuador.
  • C. E
    The E is a New York City Subway line that runs between Queens and Manhattan, providing a key rapid transit connection used by AirTrain JFK passengers traveling to and from the city.
  • D. EW
    EW is the common abbreviation for Entertainment Weekly, a popular American magazine and website covering movies, television, music, books, and pop culture.
  • E. BE
    BE is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Belgium in international standards and systems.
  • 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: [United States Department of Education, abbreviation, ED]
Generated description
ED is the federal agency responsible for establishing policy, administering, and coordinating most education-related programs in the United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ED
Target entity description: ED is the federal agency responsible for establishing policy, administering, and coordinating most education-related programs in the United States.
  • A. Ed
    Ed is a common masculine given name, typically used as a short form of names such as Edward, Edwin, or Edmund.
  • B. EC
    EC is the two-letter ISO 3166-1 alpha-2 country code assigned to Ecuador.
  • C. E
    The E is a New York City Subway line that runs between Queens and Manhattan, providing a key rapid transit connection used by AirTrain JFK passengers traveling to and from the city.
  • D. EW
    EW is the common abbreviation for Entertainment Weekly, a popular American magazine and website covering movies, television, music, books, and pop culture.
  • E. BE
    BE is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Belgium in international standards and systems.
  • 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_69a25737567c81908f9c505300239181 completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25be5a6d081909723b23a6361d6ea completed Feb. 28, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3232f11a08190ad532c68d9e8e2da completed Feb. 28, 2026, 5:17 p.m.
NEDg Description generation batch_69a3244be2b48190a44c07f04ddc623d completed Feb. 28, 2026, 5:22 p.m.
NED2 Entity disambiguation (via description) batch_69a324b5516c8190bda5ecb3c4c0d370 completed Feb. 28, 2026, 5:24 p.m.
Created at: Feb. 28, 2026, 2:51 a.m.