Triple

T8018054
Position Surface form Disambiguated ID Type / Status
Subject Pessac E186669 entity
Predicate hasTwinTown P919 FINISHED
Object Gondomar E699876 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: Gondomar | Statement: [Pessac, hasTwinTown, Gondomar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gondomar
Context triple: [Pessac, hasTwinTown, Gondomar]
  • A. Gondomar chosen
    Gondomar is a municipality in Portugal’s Porto District, known for its proximity to Porto and its traditional goldsmithing and jewelry industry.
  • B. Henares
    Henares is a river in central Spain that flows through the Province of Guadalajara and is a tributary of the Jarama River.
  • C. San Sebastián de los Reyes
    San Sebastián de los Reyes is a municipality in central Spain known for its proximity to Madrid and its traditional bull-running festivities.
  • D. Jerez de García Salinas
    Jerez de García Salinas is a historic colonial town and important agricultural and cultural center in the Mexican state of Zacatecas.
  • E. Alhué
    Alhué is a rural commune and town in central Chile known for its agricultural activities and traditional countryside character within the Santiago Metropolitan Region.
  • 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_69ca82ac7fc081909b1398cf025423af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3df626e8819098a9f8908dfdad3b completed March 31, 2026, 3:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc56c213ec8190b3bd96c42d1357e4 completed March 31, 2026, 11:20 p.m.
Created at: March 30, 2026, 5:20 p.m.