Triple

T9259378
Position Surface form Disambiguated ID Type / Status
Subject Tienen E222533 entity
Predicate hasFrenchName P744 FINISHED
Object Tirlemont
Tirlemont is the French name for Tienen, a historic city in the Flemish Brabant province of Belgium known for its sugar industry.
E788970 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: Tirlemont | Statement: [Tienen, hasFrenchName, Tirlemont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tirlemont
Context triple: [Tienen, hasFrenchName, Tirlemont]
  • A. Moensberg
    Moensberg is a residential neighborhood in the municipality of Uccle in the Brussels-Capital Region of Belgium.
  • B. Lannesdorf
    Lannesdorf is a residential subdistrict of the Bad Godesberg borough in the city of Bonn, Germany.
  • C. Malmedy
    Malmedy is a historic town and municipality in eastern Belgium, known for its Ardennes setting, traditional carnival, and proximity to the Battle of the Bulge sites.
  • D. Schorisse
    Schorisse is a village in East Flanders, Belgium, that now forms part of the municipality of Maarkedal.
  • E. Drimmelen
    Drimmelen is a municipality and village in the southern Netherlands, known for its historic harbor and as a gateway to the Biesbosch National Park.
  • 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: Tirlemont
Triple: [Tienen, hasFrenchName, Tirlemont]
Generated description
Tirlemont is the French name for Tienen, a historic city in the Flemish Brabant province of Belgium known for its sugar industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tirlemont
Target entity description: Tirlemont is the French name for Tienen, a historic city in the Flemish Brabant province of Belgium known for its sugar industry.
  • A. Moensberg
    Moensberg is a residential neighborhood in the municipality of Uccle in the Brussels-Capital Region of Belgium.
  • B. Lannesdorf
    Lannesdorf is a residential subdistrict of the Bad Godesberg borough in the city of Bonn, Germany.
  • C. Malmedy
    Malmedy is a historic town and municipality in eastern Belgium, known for its Ardennes setting, traditional carnival, and proximity to the Battle of the Bulge sites.
  • D. Schorisse
    Schorisse is a village in East Flanders, Belgium, that now forms part of the municipality of Maarkedal.
  • E. Drimmelen
    Drimmelen is a municipality and village in the southern Netherlands, known for its historic harbor and as a gateway to the Biesbosch National Park.
  • 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_69ca841e4cd481908e738c74e958eaea completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd0714317481908405f857a4f49e74 completed April 1, 2026, 11:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69d09bf225608190ade085302946dd8f completed April 4, 2026, 5:04 a.m.
NEDg Description generation batch_69d09dc3ccb08190a70e278a67249070 completed April 4, 2026, 5:12 a.m.
NED2 Entity disambiguation (via description) batch_69d09e3f211c819087b9e75f0d8faf93 completed April 4, 2026, 5:14 a.m.
Created at: March 30, 2026, 7:32 p.m.