Triple

T13679295
Position Surface form Disambiguated ID Type / Status
Subject SU Agen Lot-et-Garonne E327956 entity
Predicate cityOfHomeGround P104347 FINISHED
Object Agen E64826 NE FINISHED

How this triple was built (3 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: [SU Agen Lot-et-Garonne, cityOfHomeGround, Agen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Agen
Context triple: [SU Agen Lot-et-Garonne, cityOfHomeGround, Agen]
  • A. Agen chosen
    Agen is a historic town in southwestern France known for its prunes and location between Bordeaux and Toulouse.
  • B. Agen canton
    Agen canton is an administrative division in the Lot-et-Garonne department of southwestern France, centered around the city of Agen.
  • C. Argeo
    Argeo is the given first name of Paul Cellucci, an American politician and former Governor of Massachusetts.
  • D. Agaja
    Agaja was an 18th-century king of the Kingdom of Dahomey in West Africa, known for expanding the kingdom’s power and centralizing its political and military structures.
  • E. Ageo
    Ageo is a city in Japan known as a residential and industrial hub within the Greater Tokyo metropolitan area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: cityOfHomeGround
Context triple: [SU Agen Lot-et-Garonne, cityOfHomeGround, Agen]
  • A. occasionalHomeGroundCity
    Indicates that a location serves as a non-primary or infrequent home ground city for an entity, such as a sports team or organization.
  • B. primaryHomeGroundNot
    Indicates that the specified location is explicitly not the entity’s primary home ground.
  • C. cityOfStadium
    Indicates that a stadium is located in, or primarily associated with, a particular city.
  • D. clubStadiumCity chosen
    Indicates the city where a club’s home stadium is located.
  • E. homeStadiumOf
    Indicates that a particular stadium serves as the primary home venue for a specific sports team or organization.
  • F. None of above.

Provenance (4 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc66cbb088190907cb89dda8e4ebd completed April 12, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdeed4548819082038c5b88ccd212 completed May 7, 2026, 6:50 p.m.
PD Predicate disambiguation batch_69dbbe8d8d0881908d6e89954f44eed4 completed April 12, 2026, 3:47 p.m.
Created at: April 9, 2026, 9:53 p.m.