Triple

T17018059
Position Surface form Disambiguated ID Type / Status
Subject Night on Earth E412871 entity
Predicate mainCastMember P5563 FINISHED
Object Matti Pellonpää
Matti Pellonpää was a Finnish actor known for his distinctive roles in European art-house cinema, particularly in the films of Aki Kaurismäki.
E1252674 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: Matti Pellonpää | Statement: [Night on Earth, mainCastMember, Matti Pellonpää]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matti Pellonpää
Context triple: [Night on Earth, mainCastMember, Matti Pellonpää]
  • A. Heikki Ojansuu
    Heikki Ojansuu was a Finnish linguist and scholar known for his research and documentation of Finnic languages and dialects.
  • B. Antti Järvenpää
    Antti Järvenpää is a Finnish public administrator who serves as the municipal manager of the municipality of Ruovesi.
  • C. Matti Saari
    Matti Saari is a Finnish official who served as the governor of the former Western Finland Province.
  • D. Paavo Pylkkänen
    Paavo Pylkkänen is a Finnish philosopher of mind known for his work on quantum theory and consciousness, particularly in relation to David Bohm’s ideas.
  • E. Hannu Heikkinen
    Hannu Heikkinen is a structural engineer known for his work on the design and construction of Toronto City Hall.
  • 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: Matti Pellonpää
Triple: [Night on Earth, mainCastMember, Matti Pellonpää]
Generated description
Matti Pellonpää was a Finnish actor known for his distinctive roles in European art-house cinema, particularly in the films of Aki Kaurismäki.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Matti Pellonpää
Target entity description: Matti Pellonpää was a Finnish actor known for his distinctive roles in European art-house cinema, particularly in the films of Aki Kaurismäki.
  • A. Heikki Ojansuu
    Heikki Ojansuu was a Finnish linguist and scholar known for his research and documentation of Finnic languages and dialects.
  • B. Antti Järvenpää
    Antti Järvenpää is a Finnish public administrator who serves as the municipal manager of the municipality of Ruovesi.
  • C. Matti Saari
    Matti Saari is a Finnish official who served as the governor of the former Western Finland Province.
  • D. Paavo Pylkkänen
    Paavo Pylkkänen is a Finnish philosopher of mind known for his work on quantum theory and consciousness, particularly in relation to David Bohm’s ideas.
  • E. Hannu Heikkinen
    Hannu Heikkinen is a structural engineer known for his work on the design and construction of Toronto City Hall.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d480a58c8190a3912d26debb4311 completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01413cc6f08190ae83a0c98fb96b90 completed May 11, 2026, 2:38 a.m.
NEDg Description generation batch_6a014218d0cc81909c1b1b4c11484364 completed May 11, 2026, 2:42 a.m.
NED2 Entity disambiguation (via description) batch_6a01427ce5d08190b383ea907ca3352e completed May 11, 2026, 2:44 a.m.
Created at: April 10, 2026, 5:33 a.m.