Triple

T9914903
Position Surface form Disambiguated ID Type / Status
Subject Jean Gabin E185842 entity
Predicate notableWork P4 FINISHED
Object Le Président
Le Président is a 1961 French political drama film starring Jean Gabin as an aging former prime minister confronting corruption and his own legacy.
E829733 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: Le Président | Statement: [Jean Gabin, notableWork, Le Président]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Le Président
Context triple: [Jean Gabin, notableWork, Le Président]
  • A. Mr. President
    "Mr. President" is the formal style of address used for the head of state of the Russian Federation.
  • B. Mr. President
    "Mr. President" is the formal style of address used for the head of state of Austria.
  • C. Mr. President
    "Mr. President" is the formal style of address used for the presiding officer of the Chamber of Deputies.
  • D. Mr. President
    Mr. President is the formal style of address used for the head of state of Algeria.
  • E. Mr. President
    "Mr. President" is the formal style of address used for the presiding officer of the Massachusetts Senate.
  • 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: Le Président
Triple: [Jean Gabin, notableWork, Le Président]
Generated description
Le Président is a 1961 French political drama film starring Jean Gabin as an aging former prime minister confronting corruption and his own legacy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Le Président
Target entity description: Le Président is a 1961 French political drama film starring Jean Gabin as an aging former prime minister confronting corruption and his own legacy.
  • A. Mr. President
    "Mr. President" is the formal style of address used for the head of state of the Russian Federation.
  • B. Mr. President
    "Mr. President" is the formal style of address used for the head of state of Austria.
  • C. Mr. President
    "Mr. President" is the formal style of address used for the presiding officer of the Chamber of Deputies.
  • D. Mr. President
    Mr. President is the formal style of address used for the head of state of Algeria.
  • E. Mr. President
    "Mr. President" is the formal style of address used for the presiding officer of the Massachusetts Senate.
  • 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_69ca829b45f481909040f7b99a1976ed completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb53ba1ac8190ba655133b81596d7 completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20dd82edc8190b405a3969864af77 completed April 5, 2026, 7:23 a.m.
NEDg Description generation batch_69d20ed1f69c819099faa881a9a4368d completed April 5, 2026, 7:27 a.m.
NED2 Entity disambiguation (via description) batch_69d212e3b864819092b8464f5a5ab696 completed April 5, 2026, 7:44 a.m.
Created at: March 30, 2026, 8:41 p.m.