Triple

T4042420
Position Surface form Disambiguated ID Type / Status
Subject Marmande E83980 entity
Predicate locatedNear P294 FINISHED
Object Agen E64826 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: Agen | Statement: [Marmande, locatedNear, Agen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Agen
Context triple: [Marmande, locatedNear, Agen]
  • A. Agen chosen
    Agen is a historic town in southwestern France known for its prunes and location between Bordeaux and Toulouse.
  • B. Ageo
    Ageo is a city in Japan known as a residential and industrial hub within the Greater Tokyo metropolitan area.
  • C. Agutaynen
    Agutaynen is an Austronesian language spoken by the Agutaynen people in the Philippines, primarily in the province of Palawan.
  • D. Agta
    The Agta are an indigenous Negrito people of the Philippines known for their traditionally nomadic, forest-based lifestyle and rich oral traditions.
  • E. Inagi
    Inagi is a suburban city in western Tokyo, Japan, known for its residential neighborhoods and proximity to the Tama River.
  • 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_69aed92f7cf0819098e0539bdcc3767f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb5b65c08190ba3f340ed18737f8 completed March 9, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5564d0fb881909ba645714be27b95 completed March 14, 2026, 12:36 p.m.
Created at: March 9, 2026, 3:37 p.m.