Triple

T34853069
Position Surface form Disambiguated ID Type / Status
Subject fête des Filets Bleus E1004651 entity
Predicate metEnAvant P181922 FINISHED
Object patrimoine maritime de Concarneau LITERAL 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: patrimoine maritime de Concarneau | Statement: [fête des Filets Bleus, metEnAvant, patrimoine maritime de Concarneau]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: metEnAvant
Context triple: [fête des Filets Bleus, metEnAvant, patrimoine maritime de Concarneau]
  • A. metOn
    Indicates that two or more entities encountered each other at the same time and place for the first time or for a particular meeting.
  • B. metThrough
    Indicates that two entities became acquainted or connected as a result of an intermediary person, event, platform, or context through which they first met.
  • C. metBetween
    Indicates that two or more entities had an in-person or virtual meeting or encounter with each other during a specified time or context.
  • D. metrizes
    Indicates that a given metric defines or induces the topology or structure on a space, making that metric compatible with and fully characterizing the space’s topological properties.
  • E. metro
    Indicates a relationship where an entity is associated with, located in, or served by a metropolitan transit system (such as a subway or urban rail network).
  • F. None of above. chosen

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_69f76dba76f0819090643cba102c41ec completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f782f4f10081908f97f6d0d2dbeec7 completed May 3, 2026, 5:16 p.m.
PD Predicate disambiguation batch_69f780ff71cc8190a67e71076fbad81a completed May 3, 2026, 5:08 p.m.
PDg Predicate description generation batch_69f782f416c081908bdd9b1ad456f0e2 completed May 3, 2026, 5:16 p.m.
Created at: May 3, 2026, 4 p.m.