Triple

T38243511

Position	Surface form	Disambiguated ID	Type / Status
Subject	Pont Samson	`E1013831`	entity
Predicate	localisationUrbaine	`P51099`	FINISHED
Object	centre-ville de Bayeux Le centre-ville de Bayeux est le cœur historique et commerçant de la ville normande de Bayeux, connu pour ses ruelles anciennes, ses maisons à colombages et sa proximité avec la célèbre cathédrale et la tapisserie de Bayeux.	`E2260391`	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: centre-ville de Bayeux | Statement: [Pont Samson, localisationUrbaine, centre-ville de Bayeux]

NEDg Description generation gpt-5.1

Instruction

Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"

Input

Entity: centre-ville de Bayeux
Triple: [Pont Samson, localisationUrbaine, centre-ville de Bayeux]

Generated description

Le centre-ville de Bayeux est le cœur historique et commerçant de la ville normande de Bayeux, connu pour ses ruelles anciennes, ses maisons à colombages et sa proximité avec la célèbre cathédrale et la tapisserie de Bayeux.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: localisationUrbaine
Context triple: [Pont Samson, localisationUrbaine, centre-ville de Bayeux]

A. capitalOfArrondissement
Indicates that a place serves as the administrative capital (seat) of a specified arrondissement.
B. isCommune
Indicates that an entity functions as or has the status of a commune, typically a local administrative or municipal unit.
C. isUrbanCommuneOf
Indicates that one entity is an urban commune that administratively belongs to or is part of another entity (typically a higher-level territorial unit).
D. capitalOfCommune
Indicates that one place serves as the administrative capital or chief town of a given commune.
E. hasCommune chosen
Indicates a relationship where an entity is associated with, belongs to, or is located within a specific commune (municipal administrative unit).
F. None of above.

Provenance (6 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_69f76dd7e89c8190b7866bc85aea521b`	completed	May 3, 2026, 3:46 p.m.
NER	Named-entity recognition	`batch_69fcef654d588190b29ecc76678d1aa0`	completed	May 7, 2026, 8 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a4185635b3c81909fa8ae4a354102da`	completed	June 28, 2026, 8:34 p.m.
NEDg	Description generation	`batch_6a418629fdd88190869fffe5efa3fe59`	completed	June 28, 2026, 8:38 p.m.
NED2	Entity disambiguation (via description)	`batch_6a4186a6b2988190bada9bfa20bc2eee`	completed	June 28, 2026, 8:40 p.m.
PD	Predicate disambiguation	`batch_69fcecdb97f48190b382b7d13be92dc0`	completed	May 7, 2026, 7:49 p.m.

Created at: May 3, 2026, 4:30 p.m.