Triple

T664531
Position Surface form Disambiguated ID Type / Status
Subject Tulle E12829 entity
Predicate connectedByRailTo P848 FINISHED
Object Ussel
Ussel is a small commune in central France known as a local administrative and service center in the Corrèze department of the Nouvelle-Aquitaine region.
 E104980 NE FINISHED

How this triple was built (4 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: Ussel | Statement: [Tulle, connectedByRailTo, Ussel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ussel
Context triple: [Tulle, connectedByRailTo, Ussel]
  • A. Aurillac
    Aurillac is a historic town in south-central France, known as the capital of the Cantal department and for its traditional umbrella-making industry.
  • B. Alès
    Alès is a historic industrial town in southern France, located at the foot of the Cévennes mountains.
  • C. Vallauris
    Vallauris is a town in the French Riviera renowned for its pottery tradition and its association with Pablo Picasso, who lived and worked there for several years.
  • D. Veyrier
    Veyrier is a municipality in southwestern Switzerland located just outside the city of Geneva, near the French border.
  • E. Bourgueil
    Bourgueil is a Loire Valley wine appellation in France renowned for its red wines, particularly those made predominantly from Cabernet Franc.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Ussel
Triple: [Tulle, connectedByRailTo, Ussel]
Generated description
Ussel is a small commune in central France known as a local administrative and service center in the Corrèze department of the Nouvelle-Aquitaine region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ussel
Target entity description: Ussel is a small commune in central France known as a local administrative and service center in the Corrèze department of the Nouvelle-Aquitaine region.
  • A. Aurillac
    Aurillac is a historic town in south-central France, known as the capital of the Cantal department and for its traditional umbrella-making industry.
  • B. Alès
    Alès is a historic industrial town in southern France, located at the foot of the Cévennes mountains.
  • C. Vallauris
    Vallauris is a town in the French Riviera renowned for its pottery tradition and its association with Pablo Picasso, who lived and worked there for several years.
  • D. Veyrier
    Veyrier is a municipality in southwestern Switzerland located just outside the city of Geneva, near the French border.
  • E. Bourgueil
    Bourgueil is a Loire Valley wine appellation in France renowned for its red wines, particularly those made predominantly from Cabernet Franc.
  • F. None of above. chosen

Provenance (5 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_69a493355dec819098d4244b2fa34885 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49fd3d8fc8190866af5c76c08f486 completed March 1, 2026, 8:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c0036a5081909d5b3a81a9ef3daf completed March 4, 2026, 5:15 a.m.
NEDg Description generation batch_69a7c0716e708190b907502b17b671f8 completed March 4, 2026, 5:17 a.m.
NED2 Entity disambiguation (via description) batch_69a7c0d166ac819089b683e7cee92043 completed March 4, 2026, 5:19 a.m.
Created at: March 1, 2026, 7:36 p.m.