Triple

T2992067
Position Surface form Disambiguated ID Type / Status
Subject Beauvais–Tillé Airport E80779 entity
Predicate locatedIn P40 FINISHED
Object Tillé
Tillé is a commune in northern France best known for hosting Beauvais–Tillé Airport, a secondary hub for low-cost flights serving the Paris region.
 E317403 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: Tillé | Statement: [Beauvais–Tillé Airport, locatedIn, Tillé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tillé
Context triple: [Beauvais–Tillé Airport, locatedIn, Tillé]
  • A. Schierke
    Schierke is a small village in the Harz Mountains of Germany, known as a gateway to the Brocken peak and for its historic narrow-gauge railway connections and winter sports tourism.
  • B. Tullistes
    Tullistes are the inhabitants of the French city of Tulle, located in the Corrèze department in central France.
  • C. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • D. Tilo
    Tilo is a central, enigmatic figure in Arundhati Roy’s novel "The Ministry of Utmost Happiness," whose complex personal history and relationships anchor much of the book’s emotional and political narrative.
  • E. Celle
    Celle is a historic town in northern Germany renowned for its well-preserved half-timbered old town and ducal palace.
  • 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: Tillé
Triple: [Beauvais–Tillé Airport, locatedIn, Tillé]
Generated description
Tillé is a commune in northern France best known for hosting Beauvais–Tillé Airport, a secondary hub for low-cost flights serving the Paris region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tillé
Target entity description: Tillé is a commune in northern France best known for hosting Beauvais–Tillé Airport, a secondary hub for low-cost flights serving the Paris region.
  • A. Schierke
    Schierke is a small village in the Harz Mountains of Germany, known as a gateway to the Brocken peak and for its historic narrow-gauge railway connections and winter sports tourism.
  • B. Tullistes
    Tullistes are the inhabitants of the French city of Tulle, located in the Corrèze department in central France.
  • C. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • D. Tilo
    Tilo is a central, enigmatic figure in Arundhati Roy’s novel "The Ministry of Utmost Happiness," whose complex personal history and relationships anchor much of the book’s emotional and political narrative.
  • E. Celle
    Celle is a historic town in northern Germany renowned for its well-preserved half-timbered old town and ducal palace.
  • 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_69ad8b16c3488190b47b6aa7a59a335b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99df69d08190a0e25efb0dc8d653 completed March 8, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b109039cfc8190a286c83df752967e completed March 11, 2026, 6:17 a.m.
NEDg Description generation batch_69b10bc71c708190b1e620d41278c3e0 completed March 11, 2026, 6:29 a.m.
NED2 Entity disambiguation (via description) batch_69b10c43a7c48190b63a7b3f0f180d44 completed March 11, 2026, 6:31 a.m.
Created at: March 8, 2026, 2:59 p.m.