Triple

T10225545
Position Surface form Disambiguated ID Type / Status
Subject Empire Records E243193 entity
Predicate character P662 FINISHED
Object Mark
Mark is a quirky, music-obsessed employee at the independent record store in the 1995 cult film "Empire Records," known for his goofy charm and laid-back attitude.
E852776 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: Mark | Statement: [Empire Records, character, Mark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mark
Context triple: [Empire Records, character, Mark]
  • A. Mark
    Mark is the given name of Mark Zuckerberg, the American technology entrepreneur and co-founder of Facebook.
  • B. Mark
    Mark is a punctuation symbol used in writing systems, including those that employ the Cyrillic Extended-B Unicode block.
  • C. Mark
    The Mark was the basic unit of currency used in Germany during various historical periods, including the era of the Papiermark.
  • D. Mark
    Mark is a river in the southern Netherlands and northern Belgium that flows through the province of North Brabant before joining the Dintel.
  • E. Mark
    Mark is one of the four canonical Gospels in the New Testament, traditionally attributed to John Mark and known for its concise, fast-paced account of the life, ministry, death, and resurrection of Jesus Christ.
  • 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: Mark
Triple: [Empire Records, character, Mark]
Generated description
Mark is a quirky, music-obsessed employee at the independent record store in the 1995 cult film "Empire Records," known for his goofy charm and laid-back attitude.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mark
Target entity description: Mark is a quirky, music-obsessed employee at the independent record store in the 1995 cult film "Empire Records," known for his goofy charm and laid-back attitude.
  • A. Mark
    Mark is the given name of Mark Zuckerberg, the American technology entrepreneur and co-founder of Facebook.
  • B. Mark
    Mark is one of the four canonical Gospels in the New Testament, traditionally attributed to John Mark and known for its concise, fast-paced account of the life, ministry, death, and resurrection of Jesus Christ.
  • C. Mark
    Mark is a common masculine given name of Latin origin, derived from Marcus and historically associated with figures such as the evangelist Saint Mark.
  • D. Mark
    Mark is a punctuation symbol used in writing systems, including those that employ the Cyrillic Extended-B Unicode block.
  • E. Mark
    The Mark was the basic unit of currency used in Germany during various historical periods, including the era of the Papiermark.
  • 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_69d381b0f97c819085c9b45799a5fb7c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d1f9cf6c81909a6b9e9b9d0a79fe completed April 7, 2026, 9:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f715bea881909da9d0749fa6420f completed April 9, 2026, 12:47 a.m.
NEDg Description generation batch_69d6fcaa16788190a4c7ef79a78febc6 completed April 9, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_69d6fd6d705c81908e469068937a79b3 completed April 9, 2026, 1:14 a.m.
Created at: April 6, 2026, 11:17 a.m.