Triple

T13076346
Position Surface form Disambiguated ID Type / Status
Subject Terence Marsh E329585 entity
Predicate familyName P18 FINISHED
Object Marsh
Marsh is a common English surname of Old French origin, typically referring to someone who lived near a marsh or wetland.
 E610325 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: Marsh | Statement: [Terence Marsh, familyName, Marsh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marsh
Context triple: [Terence Marsh, familyName, Marsh]
  • A. Marsh
    Marsh is the maiden surname of American country music singer and songwriter Dottie West.
  • B. Marsh
    Marsh is a surname most notably associated with Mae Marsh, an American silent film actress renowned for her roles in early 20th-century cinema.
  • C. Marsh
    Marsh is the middle name of William Marsh Rice, the American businessman and philanthropist who founded Rice University in Houston, Texas.
  • D. Marsh
    Marsh is a global insurance brokerage and risk management firm providing advisory and brokerage services to businesses and individuals worldwide.
  • E. Marshlands
    Marshlands are expansive wetland ecosystems characterized by waterlogged soils and dense aquatic vegetation, providing critical habitats for diverse wildlife and supporting traditional human livelihoods.
  • 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: Marsh
Triple: [Terence Marsh, familyName, Marsh]
Generated description
Marsh is a common English surname of Old French origin, typically referring to someone who lived near a marsh or wetland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marsh
Target entity description: Marsh is a common English surname of Old French origin, typically referring to someone who lived near a marsh or wetland.
  • A. Marsh
    Marsh is the middle name of William Marsh Rice, the American businessman and philanthropist who founded Rice University in Houston, Texas.
  • B. Marsh
    Marsh is the maiden surname of American country music singer and songwriter Dottie West.
  • C. Marsh
    Marsh is a global insurance brokerage and risk management firm providing advisory and brokerage services to businesses and individuals worldwide.
  • D. Marsh chosen
    Marsh is a surname most notably associated with Mae Marsh, an American silent film actress renowned for her roles in early 20th-century cinema.
  • E. Marshlands
    Marshlands are expansive wetland ecosystems characterized by waterlogged soils and dense aquatic vegetation, providing critical habitats for diverse wildlife and supporting traditional human livelihoods.
  • F. None of above.

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_69d80771749c81909a6d9197b9504872 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d98117209081908272021013df2222 completed April 10, 2026, 11 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d608a2288190bf07023a5303f887 completed May 3, 2026, 4:58 a.m.
NEDg Description generation batch_69f6d6e326408190b7906c7ea8e3ef85 completed May 3, 2026, 5:02 a.m.
NED2 Entity disambiguation (via description) batch_69f6d873b978819097962c82e8ffdac8 completed May 3, 2026, 5:09 a.m.
Created at: April 9, 2026, 9:01 p.m.