Triple

T117192
Position Surface form Disambiguated ID Type / Status
Subject Engineering Management Division E2366 entity
Predicate shortName P43 FINISHED
Object EMD
EMD is the commonly used abbreviation for the Engineering Management Division, a professional group focused on the practice and advancement of engineering management.
 E11977 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: EMD | Statement: [Engineering Management Division, shortName, EMD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: EMD
Context triple: [Engineering Management Division, shortName, EMD]
  • A. MARC Train
    MARC Train is a commuter rail service operating in Maryland and the surrounding region, connecting cities such as Washington, D.C., Baltimore, and Martinsburg.
  • B. AMX
    AMX is a Dutch stock market index that tracks the performance of mid-cap companies listed on Euronext Amsterdam.
  • C. Audion
    Audion is an early triode vacuum tube invented by Lee de Forest that enabled the amplification of electrical signals and was crucial to the development of radio and electronics.
  • D. TNT
    TNT is an American cable television network known for airing sports, movies, and original drama programming.
  • E. FRA
    FRA is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies France in international standards and data 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: EMD
Triple: [Engineering Management Division, shortName, EMD]
Generated description
EMD is the commonly used abbreviation for the Engineering Management Division, a professional group focused on the practice and advancement of engineering management.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: EMD
Target entity description: EMD is the commonly used abbreviation for the Engineering Management Division, a professional group focused on the practice and advancement of engineering management.
  • A. MARC Train
    MARC Train is a commuter rail service operating in Maryland and the surrounding region, connecting cities such as Washington, D.C., Baltimore, and Martinsburg.
  • B. AMX
    AMX is a Dutch stock market index that tracks the performance of mid-cap companies listed on Euronext Amsterdam.
  • C. Audion
    Audion is an early triode vacuum tube invented by Lee de Forest that enabled the amplification of electrical signals and was crucial to the development of radio and electronics.
  • D. TNT
    TNT is an American cable television network known for airing sports, movies, and original drama programming.
  • E. FRA
    FRA is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies France in international standards and data 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_69a2506c5428819085c28a8884790e29 completed Feb. 28, 2026, 2:18 a.m.
NER Named-entity recognition batch_69a257133a848190869dea4ab2009fc4 completed Feb. 28, 2026, 2:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69a285012e5881909b19f6c49a2373e1 completed Feb. 28, 2026, 6:02 a.m.
NEDg Description generation batch_69a2855c20148190986af3f8ecbbfa3e completed Feb. 28, 2026, 6:04 a.m.
NED2 Entity disambiguation (via description) batch_69a285eb39388190908db5db5673dde7 completed Feb. 28, 2026, 6:06 a.m.
Created at: Feb. 28, 2026, 2:24 a.m.