Triple

T31530702
Position Surface form Disambiguated ID Type / Status
Subject Marie-Octobre E804469 entity
Predicate characterPlayedBy_Paul Meurisse P9616 FINISHED
Object Lucien Marinval
Lucien Marinval is a central character in the 1959 French thriller film "Marie-Octobre," portrayed as one of the former Resistance members reunited years after the war to uncover a traitor among them.
 E2286304 NE FINISHED

How this triple was built (3 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: Lucien Marinval | Statement: [Marie-Octobre, characterPlayedBy_Paul Meurisse, Lucien Marinval]
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: Lucien Marinval
Triple: [Marie-Octobre, characterPlayedBy_Paul Meurisse, Lucien Marinval]
Generated description
Lucien Marinval is a central character in the 1959 French thriller film "Marie-Octobre," portrayed as one of the former Resistance members reunited years after the war to uncover a traitor among them.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: characterPlayedBy_Paul Meurisse
Context triple: [Marie-Octobre, characterPlayedBy_Paul Meurisse, Lucien Marinval]
  • A. characterPlayedByEdwardMulhare
    Indicates that the subject is a character that was portrayed or played by Edward Mulhare.
  • B. characterPlayedBy Emmanuelle Chriqui
    Indicates that the role or character in question is portrayed or acted by Emmanuelle Chriqui.
  • C. playedBy chosen
    Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
  • D. characterPlayedByRichardHarris
    Indicates that the subject is a character that was portrayed by the actor Richard Harris.
  • E. characterPlayedByNicholasHamilton
    Indicates that the subject is a character portrayed by the actor Nicholas Hamilton.
  • F. None of above.

Provenance (6 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_69f348d03ef88190a2b73d7b94b9e02d completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69fe831c97c88190b27ecf100e25c2a0 completed May 9, 2026, 12:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a469fc2472081909470e2d7805eaafc completed July 2, 2026, 5:28 p.m.
NEDg Description generation batch_6a46a1bb8d708190b4190000b10e75c4 completed July 2, 2026, 5:37 p.m.
NED2 Entity disambiguation (via description) batch_6a46a597aa24819084036fcc4bcb7955 completed July 2, 2026, 5:53 p.m.
PD Predicate disambiguation batch_69fe7f1b92648190b14e56bcaee5d0ca completed May 9, 2026, 12:26 a.m.
Created at: April 30, 2026, 10:01 p.m.