Triple

T317476
Position Surface form Disambiguated ID Type / Status
Subject Peter Lorre E7738 entity
Predicate notableWork P4 FINISHED
Object M
M is a landmark 1931 German thriller directed by Fritz Lang, renowned as one of the earliest and most influential films about a serial killer and for its innovative use of sound and expressionist style.
 E35617 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: M | Statement: [Peter Lorre, notableWork, M]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: M
Context triple: [Peter Lorre, notableWork, M]
  • A. M
    M is a functional data mashup and query language used in Microsoft Power BI and related tools for data transformation and preparation.
  • B. Ma
    Ma is a common Chinese surname borne by many notable individuals across fields such as music, politics, and sports.
  • C. MR
    MR is a Belgian French-speaking liberal political party that participated as one of the partners in the federal Vivaldi coalition government led by Alexander De Croo.
  • D. MP
    MP is the two-letter ISO 3166-1 alpha-2 country code assigned to the Northern Mariana Islands.
  • E. J
    J is a New York City Subway service that runs through Brooklyn and Queens into Manhattan, serving neighborhoods in eastern Brooklyn and southern Queens.
  • 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: M
Triple: [Peter Lorre, notableWork, M]
Generated description
M is a landmark 1931 German thriller directed by Fritz Lang, renowned as one of the earliest and most influential films about a serial killer and for its innovative use of sound and expressionist style.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: M
Target entity description: M is a landmark 1931 German thriller directed by Fritz Lang, renowned as one of the earliest and most influential films about a serial killer and for its innovative use of sound and expressionist style.
  • A. M chosen
    M is a functional data mashup and query language used in Microsoft Power BI and related tools for data transformation and preparation.
  • B. Ma
    Ma is a common Chinese surname borne by many notable individuals across fields such as music, politics, and sports.
  • C. MR
    MR is a Belgian French-speaking liberal political party that participated as one of the partners in the federal Vivaldi coalition government led by Alexander De Croo.
  • D. MP
    MP is the two-letter ISO 3166-1 alpha-2 country code assigned to the Northern Mariana Islands.
  • E. J
    J is a New York City Subway service that runs through Brooklyn and Queens into Manhattan, serving neighborhoods in eastern Brooklyn and southern Queens.
  • F. None of above.

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_69a2e7e7af7881908890039d6be4e9b8 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ea65ca7081908093e6aaaf2d34f7 completed Feb. 28, 2026, 1:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3c8b8d7d88190b43f7b6b0289445f completed March 1, 2026, 5:03 a.m.
NEDg Description generation batch_69a3c964b7a48190afa7cada4a499739 completed March 1, 2026, 5:06 a.m.
NED2 Entity disambiguation (via description) batch_69a3c9bc3eec81909e6d1b7af6cf7d58 completed March 1, 2026, 5:08 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.