Triple

T14476831
Position Surface form Disambiguated ID Type / Status
Subject What Where E358994 entity
Predicate featuresCharacter P626 FINISHED
Object Bem
Bem is a character from the "What Where" segment of Samuel Beckett’s television play, representing one of the indistinct figures involved in its cryptic, minimalist drama.
 E1101769 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: Bem | Statement: [What Where, featuresCharacter, Bem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bem
Context triple: [What Where, featuresCharacter, Bem]
  • A. Bek
    Bek is a short or informal given name, typically used as a diminutive of Rebekah.
  • B. Bec
    Bec is a historic Benedictine abbey in Normandy, France, renowned as a major medieval center of learning and monastic reform.
  • C. Benn
    Benn is a surname most prominently associated with Canadian professional ice hockey player Jamie Benn.
  • D. Bast
    Bast is a feline-headed goddess from ancient Egyptian mythology, often associated with protection, warfare, and later domesticity and fertility.
  • E. Boebe
    Boebe was an ancient town in the region of Magnesia in Thessaly, Greece, known from classical sources and associated with nearby Lake Boebeis.
  • 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: Bem
Triple: [What Where, featuresCharacter, Bem]
Generated description
Bem is a character from the "What Where" segment of Samuel Beckett’s television play, representing one of the indistinct figures involved in its cryptic, minimalist drama.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bem
Target entity description: Bem is a character from the "What Where" segment of Samuel Beckett’s television play, representing one of the indistinct figures involved in its cryptic, minimalist drama.
  • A. Bek
    Bek is a short or informal given name, typically used as a diminutive of Rebekah.
  • B. Bec
    Bec is a historic Benedictine abbey in Normandy, France, renowned as a major medieval center of learning and monastic reform.
  • C. Benn
    Benn is a surname most prominently associated with Canadian professional ice hockey player Jamie Benn.
  • D. Bast
    Bast is a feline-headed goddess from ancient Egyptian mythology, often associated with protection, warfare, and later domesticity and fertility.
  • E. Boebe
    Boebe was an ancient town in the region of Magnesia in Thessaly, Greece, known from classical sources and associated with nearby Lake Boebeis.
  • 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_69d827966698819082e140837737501d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de9248edb48190a74eb032aeaac027 completed April 14, 2026, 7:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd64a0553081909fd88d8f39ed1a01 completed May 8, 2026, 4:20 a.m.
NEDg Description generation batch_69fd698579588190a49f6c7a91266117 completed May 8, 2026, 4:41 a.m.
NED2 Entity disambiguation (via description) batch_69fd6a6060488190ab5662037b52c591 completed May 8, 2026, 4:45 a.m.
Created at: April 10, 2026, 1:20 a.m.