Triple

T8155704
Position Surface form Disambiguated ID Type / Status
Subject Nine Months E190444 entity
Predicate screenwriter P2831 FINISHED
Object Mike Thompson
Mike Thompson is a screenwriter best known for his work on the romantic comedy film "Nine Months."
E717013 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: Mike Thompson | Statement: [Nine Months, screenwriter, Mike Thompson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mike Thompson
Context triple: [Nine Months, screenwriter, Mike Thompson]
  • A. John Garamendi
    John Garamendi is an American politician and public official who has served in roles including California insurance commissioner and U.S. Representative.
  • B. Jared Huffman
    Jared Huffman is a Democratic U.S. Representative from California known for his work on environmental protection, public lands, and progressive policy issues.
  • C. Matt Santos
    Matt Santos is a fictional U.S. congressman who becomes President in the television series "The West Wing."
  • D. Ron Dellums
    Ron Dellums was a prominent African American congressman and anti-war activist from California known for his leadership on civil rights, social justice, and opposition to apartheid.
  • E. Dan Lungren
    Dan Lungren is an American Republican politician and former California Attorney General who later served as a U.S. Representative in Congress.
  • 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: Mike Thompson
Triple: [Nine Months, screenwriter, Mike Thompson]
Generated description
Mike Thompson is a screenwriter best known for his work on the romantic comedy film "Nine Months."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mike Thompson
Target entity description: Mike Thompson is a screenwriter best known for his work on the romantic comedy film "Nine Months."
  • A. John Garamendi
    John Garamendi is an American politician and public official who has served in roles including California insurance commissioner and U.S. Representative.
  • B. Jared Huffman
    Jared Huffman is a Democratic U.S. Representative from California known for his work on environmental protection, public lands, and progressive policy issues.
  • C. Matt Santos
    Matt Santos is a fictional U.S. congressman who becomes President in the television series "The West Wing."
  • D. Ron Dellums
    Ron Dellums was a prominent African American congressman and anti-war activist from California known for his leadership on civil rights, social justice, and opposition to apartheid.
  • E. Dan Lungren
    Dan Lungren is an American Republican politician and former California Attorney General who later served as a U.S. Representative in Congress.
  • 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_69ca82bfeb6481909d07b91b5cf69f59 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb44d725b88190b77dc7537c1fa95d completed March 31, 2026, 3:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbf0f68c88190be9aab03de6bf4a0 completed April 1, 2026, 6:45 a.m.
NEDg Description generation batch_69ccc311d4e8819080f4aeef8ee7dc3b completed April 1, 2026, 7:02 a.m.
NED2 Entity disambiguation (via description) batch_69ccd81bebf8819081b3c4efa5a9ef93 completed April 1, 2026, 8:32 a.m.
Created at: March 30, 2026, 5:37 p.m.