Triple

T14438198
Position Surface form Disambiguated ID Type / Status
Subject Poitiers–Biard Airport E358020 entity
Predicate locatedIn P40 FINISHED
Object Biard
Biard is a commune in western France, near the city of Poitiers, known for hosting the regional Poitiers–Biard Airport.
E1099319 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: Biard | Statement: [Poitiers–Biard Airport, locatedIn, Biard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Biard
Context triple: [Poitiers–Biard Airport, locatedIn, Biard]
  • A. Brummbär
    The Brummbär was a German World War II armored assault gun based on the Panzer IV chassis and armed with a heavy 150 mm howitzer for close-support urban and fortification attacks.
  • B. Loup
    The Loup is a river in southeastern France that flows through the Alpes-Maritimes department, known for its scenic gorges and popular outdoor recreation areas.
  • C. Gavrio
    Gavrio is the main port town of the Greek island of Andros in the Cyclades, serving as its primary gateway by sea.
  • D. Nattier
    Nattier is a French surname most famously associated with Jean-Marc Nattier, an 18th-century painter known for his portraits of the ladies of Louis XV’s court.
  • E. Badger
    Badger is a wise, kind, and somewhat reclusive character from Kenneth Grahame’s "The Wind in the Willows," known for offering guidance and shelter to his woodland friends.
  • 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: Biard
Triple: [Poitiers–Biard Airport, locatedIn, Biard]
Generated description
Biard is a commune in western France, near the city of Poitiers, known for hosting the regional Poitiers–Biard Airport.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Biard
Target entity description: Biard is a commune in western France, near the city of Poitiers, known for hosting the regional Poitiers–Biard Airport.
  • A. Brummbär
    The Brummbär was a German World War II armored assault gun based on the Panzer IV chassis and armed with a heavy 150 mm howitzer for close-support urban and fortification attacks.
  • B. Loup
    The Loup is a river in southeastern France that flows through the Alpes-Maritimes department, known for its scenic gorges and popular outdoor recreation areas.
  • C. Gavrio
    Gavrio is the main port town of the Greek island of Andros in the Cyclades, serving as its primary gateway by sea.
  • D. Nattier
    Nattier is a French surname most famously associated with Jean-Marc Nattier, an 18th-century painter known for his portraits of the ladies of Louis XV’s court.
  • E. Badger
    Badger is the NATO reporting name for the Soviet-era Tupolev Tu-16, a twin-engine jet strategic bomber widely used during the Cold War.
  • 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_69d8279402a88190821ffa39ae15bccf completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de914a45ec81909ab8ccf302047d7f completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bd7f46881908df1a1cea7b6af9b completed May 8, 2026, 3:43 a.m.
NEDg Description generation batch_69fd5d585cc08190908bc5f9b8abdb82 completed May 8, 2026, 3:49 a.m.
NED2 Entity disambiguation (via description) batch_69fd5e0bbd6c8190b14039b3335692c7 completed May 8, 2026, 3:52 a.m.
Created at: April 10, 2026, 1:18 a.m.