Triple

T10297835
Position Surface form Disambiguated ID Type / Status
Subject Marlborough College E241542 entity
Predicate hasAbbreviation P43 FINISHED
Object Marlb
Marlb is the commonly used abbreviation for Marlborough College, a prestigious independent boarding school in Wiltshire, England.
 E856074 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: Marlb | Statement: [Marlborough College, hasAbbreviation, Marlb]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marlb
Context triple: [Marlborough College, hasAbbreviation, Marlb]
  • A. Marl
    Marl is an industrial town in western Germany’s North Rhine-Westphalia, known for its large chemical industry complex and location within the Ruhr area.
  • B. Marden
    Marden is a surname most notably associated with the American minimalist painter Brice Marden.
  • C. Mullens
    Mullens is a surname of likely English or Irish origin borne by various individuals and families.
  • D. Marale
    Marale is a small municipality located in the Francisco Morazán Department of central Honduras.
  • E. Maasin
    Maasin is a coastal city in the Philippines that serves as the administrative, economic, and religious center of the province of Southern Leyte.
  • 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: Marlb
Triple: [Marlborough College, hasAbbreviation, Marlb]
Generated description
Marlb is the commonly used abbreviation for Marlborough College, a prestigious independent boarding school in Wiltshire, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marlb
Target entity description: Marlb is the commonly used abbreviation for Marlborough College, a prestigious independent boarding school in Wiltshire, England.
  • A. Marl
    Marl is an industrial town in western Germany’s North Rhine-Westphalia, known for its large chemical industry complex and location within the Ruhr area.
  • B. Marden
    Marden is a surname most notably associated with the American minimalist painter Brice Marden.
  • C. Mullens
    Mullens is a surname of likely English or Irish origin borne by various individuals and families.
  • D. Marale
    Marale is a small municipality located in the Francisco Morazán Department of central Honduras.
  • E. Maasin
    Maasin is a coastal city in the Philippines that serves as the administrative, economic, and religious center of the province of Southern Leyte.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2ed50908190962f0d6d049fb964 completed April 7, 2026, 9:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71d2cc9c48190bc36f6a4f8144b7f completed April 9, 2026, 3:29 a.m.
NEDg Description generation batch_69d73182d7548190ac15093aa7001db7 completed April 9, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_69d7336c06308190ac72154134a26842 completed April 9, 2026, 5:04 a.m.
Created at: April 6, 2026, 11:43 a.m.