Triple

T15991861
Position Surface form Disambiguated ID Type / Status
Subject S. Epatha Merkerson E387849 entity
Predicate familyName P18 FINISHED
Object Merkerson
Merkerson is the surname of S. Epatha Merkerson, an acclaimed American actress best known for her long-running role as Lieutenant Anita Van Buren on the television series "Law & Order."
 E1187279 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: Merkerson | Statement: [S. Epatha Merkerson, familyName, Merkerson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Merkerson
Context triple: [S. Epatha Merkerson, familyName, Merkerson]
  • A. Mackenzell
    Mackenzell is a small village in the Hesse region of central Germany.
  • B. Merkys
    Merkys is a river in Lithuania and Belarus that serves as one of the principal tributaries of the Neman (Niemen) River.
  • C. Nortrup
    Nortrup is a small municipality in Lower Saxony, Germany, situated within the Artland region.
  • D. Murck
    Murck is a character in Bertolt Brecht’s early expressionist play "Drums in the Night," which explores post–World War I disillusionment and social unrest.
  • E. Milhous
    Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
  • 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: Merkerson
Triple: [S. Epatha Merkerson, familyName, Merkerson]
Generated description
Merkerson is the surname of S. Epatha Merkerson, an acclaimed American actress best known for her long-running role as Lieutenant Anita Van Buren on the television series "Law & Order."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Merkerson
Target entity description: Merkerson is the surname of S. Epatha Merkerson, an acclaimed American actress best known for her long-running role as Lieutenant Anita Van Buren on the television series "Law & Order."
  • A. Mackenzell
    Mackenzell is a small village in the Hesse region of central Germany.
  • B. Merkys
    Merkys is a river in Lithuania and Belarus that serves as one of the principal tributaries of the Neman (Niemen) River.
  • C. Nortrup
    Nortrup is a small municipality in Lower Saxony, Germany, situated within the Artland region.
  • D. Murck
    Murck is a character in Bertolt Brecht’s early expressionist play "Drums in the Night," which explores post–World War I disillusionment and social unrest.
  • E. Milhous
    Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
  • 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_69d86daa562c81908aacc179c0fe8fb5 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e157844ed881908b42bfc1bb740d4e completed April 16, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3d3ef2881909213ff608192f1ef completed May 9, 2026, 11:31 p.m.
NEDg Description generation batch_69ffc47bce748190a651fff307aad88d completed May 9, 2026, 11:34 p.m.
NED2 Entity disambiguation (via description) batch_69ffc4e14e1881909210a78426546e88 completed May 9, 2026, 11:36 p.m.
Created at: April 10, 2026, 4:54 a.m.