Triple

T15172200
Position Surface form Disambiguated ID Type / Status
Subject Mayor of Melun E362514 entity
Predicate seat P75 FINISHED
Object Melun town hall E1142594 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: Melun town hall | Statement: [Mayor of Melun, seat, Melun town hall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Melun town hall
Context triple: [Mayor of Melun, seat, Melun town hall]
  • A. Melun town hall chosen
    Melun town hall is the main administrative building and seat of local government for the city of Melun in France.
  • B. Notre-Dame Church of Melun
    Notre-Dame Church of Melun is a historic Roman Catholic church in the town of Melun, France, noted for its medieval architecture and cultural significance.
  • C. Clermont-Ferrand City Hall
    Clermont-Ferrand City Hall is the main municipal government building of Clermont-Ferrand, France, housing the city’s administrative offices and serving as the official workplace of the mayor.
  • D. Neuilly-sur-Seine town hall
    Neuilly-sur-Seine town hall is the main municipal building and administrative center of the affluent Parisian suburb of Neuilly-sur-Seine, housing the offices of the local government and its mayor.
  • E. Nanterre town hall
    Nanterre town hall is the main municipal building and administrative center of the city of Nanterre in the western suburbs of Paris, France.
  • 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_69d85a087b7c81908baa94a53dac8d68 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e006501b488190a2ab09dbf1532571 completed April 15, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed3286a2c8190ac73b68cefd0191d completed May 9, 2026, 6:24 a.m.
Created at: April 10, 2026, 3:09 a.m.