Triple

T10496407
Position Surface form Disambiguated ID Type / Status
Subject Peter Mamakos E247548 entity
Predicate familyName P18 FINISHED
Object Mamakos
Mamakos is a Greek-origin surname most notably borne by American character actor Peter Mamakos.
 E867865 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: Mamakos | Statement: [Peter Mamakos, familyName, Mamakos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mamakos
Context triple: [Peter Mamakos, familyName, Mamakos]
  • A. Marcali
    Marcali is a small town in southwestern Hungary known for its agricultural surroundings and role as a local administrative and service center in Somogy County.
  • B. Moukari
    Moukari is a Finnish amateur radio callsign holder, identified by the callsign K9FIN Moukari.
  • C. Mamula
    Mamula is a small fortified island in the Adriatic Sea off the coast of Montenegro, known for its 19th-century Austro-Hungarian fortress and former use as a prison.
  • D. Machaon
    Machaon is a figure from Greek mythology, renowned as a skilled healer and son of the legendary physician Asclepius.
  • E. Makadara
    Makadara is a residential and commercial neighborhood in Nairobi, Kenya, known for its dense population, vibrant local markets, and mix of low- to middle-income housing.
  • 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: Mamakos
Triple: [Peter Mamakos, familyName, Mamakos]
Generated description
Mamakos is a Greek-origin surname most notably borne by American character actor Peter Mamakos.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mamakos
Target entity description: Mamakos is a Greek-origin surname most notably borne by American character actor Peter Mamakos.
  • A. Marcali
    Marcali is a small town in southwestern Hungary known for its agricultural surroundings and role as a local administrative and service center in Somogy County.
  • B. Moukari
    Moukari is a Finnish amateur radio callsign holder, identified by the callsign K9FIN Moukari.
  • C. Mamula
    Mamula is a small fortified island in the Adriatic Sea off the coast of Montenegro, known for its 19th-century Austro-Hungarian fortress and former use as a prison.
  • D. Machaon
    Machaon is a figure from Greek mythology, renowned as a skilled healer and son of the legendary physician Asclepius.
  • E. Makadara
    Makadara is a residential and commercial neighborhood in Nairobi, Kenya, known for its dense population, vibrant local markets, and mix of low- to middle-income housing.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5098cd82c8190b44127a66c9c75ae completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dcbafe9481908fb23cfdf150adac completed April 10, 2026, 11:19 a.m.
NEDg Description generation batch_69d8e8c8e360819085376d4c4ea9712d completed April 10, 2026, 12:10 p.m.
NED2 Entity disambiguation (via description) batch_69d901ef24608190934377d9dc855d6f completed April 10, 2026, 1:58 p.m.
Created at: April 6, 2026, 12:24 p.m.