Triple

T597568
Position Surface form Disambiguated ID Type / Status
Subject The Gentlemen E11419 entity
Predicate mainCharacter P1183 FINISHED
Object Dry Eye
Dry Eye is a ruthless and ambitious young Chinese-Cockney gangster who serves as one of the primary antagonists in Guy Ritchie's crime film "The Gentlemen."
 E74386 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: Dry Eye | Statement: [The Gentlemen, mainCharacter, Dry Eye]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dry Eye
Context triple: [The Gentlemen, mainCharacter, Dry Eye]
  • A. CLSCL
    CLSCL is the UN/LOCODE identifier for the port and transport location of Santiago, Chile.
  • B. Kerkinitis
    Kerkinitis is an ancient Greek colony on the Crimean coast, later known as Eupatoria, that served as an important Black Sea trading settlement.
  • C. CND
    CND is a British peace organization best known for campaigning against nuclear weapons and promoting global disarmament.
  • D. SCL
    SCL (Substation Configuration Language) is an XML-based language defined by the IEC 61850 standard for modeling, configuring, and exchanging data about electrical substations and their automation systems.
  • E. Lacringi
    The Lacringi were a lesser-known Germanic tribe that participated in the Marcomannic Wars against the Roman Empire in the 2nd century AD.
  • 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: Dry Eye
Triple: [The Gentlemen, mainCharacter, Dry Eye]
Generated description
Dry Eye is a ruthless and ambitious young Chinese-Cockney gangster who serves as one of the primary antagonists in Guy Ritchie's crime film "The Gentlemen."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dry Eye
Target entity description: Dry Eye is a ruthless and ambitious young Chinese-Cockney gangster who serves as one of the primary antagonists in Guy Ritchie's crime film "The Gentlemen."
  • A. CLSCL
    CLSCL is the UN/LOCODE identifier for the port and transport location of Santiago, Chile.
  • B. Kerkinitis
    Kerkinitis is an ancient Greek colony on the Crimean coast, later known as Eupatoria, that served as an important Black Sea trading settlement.
  • C. CND
    CND is a British peace organization best known for campaigning against nuclear weapons and promoting global disarmament.
  • D. SCL
    SCL (Substation Configuration Language) is an XML-based language defined by the IEC 61850 standard for modeling, configuring, and exchanging data about electrical substations and their automation systems.
  • E. Lacringi
    The Lacringi were a lesser-known Germanic tribe that participated in the Marcomannic Wars against the Roman Empire in the 2nd century AD.
  • 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_69a4932779b881908688590d59c71900 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49d2b98d08190a1c1e8659efdfd75 completed March 1, 2026, 8:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69a518c766508190ae39b6e254a07bc3 completed March 2, 2026, 4:57 a.m.
NEDg Description generation batch_69a5194215848190874442451c32a10b completed March 2, 2026, 4:59 a.m.
NED2 Entity disambiguation (via description) batch_69a519d2e46881909d00ff279bd4a13e completed March 2, 2026, 5:02 a.m.
Created at: March 1, 2026, 7:35 p.m.