Triple

T12775180
Position Surface form Disambiguated ID Type / Status
Subject Oedipa Maas E305349 entity
Predicate spouse P13 FINISHED
Object Mucho Maas E305352 NE FINISHED

How this triple was built (2 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: Mucho Maas | Statement: [Oedipa Maas, spouse, Mucho Maas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mucho Maas
Context triple: [Oedipa Maas, spouse, Mucho Maas]
  • A. Mucho Maas chosen
    Mucho Maas is a troubled California disc jockey and the husband of protagonist Oedipa Maas in Thomas Pynchon's novel "The Crying of Lot 49."
  • B. Maashees
    Maashees is a small village in the Dutch province of North Brabant, situated along the river Meuse and known for its rural character and historic church.
  • C. Mazama temama
    Mazama temama, commonly known as the Central American red brocket, is a small, elusive deer species native to the tropical forests of Central America and parts of southern Mexico.
  • D. Maamme
    Maamme is the national anthem of Finland, known for its patriotic lyrics and prominent role in Finnish national ceremonies and sporting events.
  • E. Maatkas
    Maatkas is a town and commune located in the mountainous Kabylie region of northern Algeria.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96df6b3c88190b0bbe70de8ddcbf3 completed April 10, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69f684fee60c81909245d4d70c9338c0 completed May 2, 2026, 11:13 p.m.
Created at: April 9, 2026, 5:29 p.m.