Triple

T2256705
Position Surface form Disambiguated ID Type / Status
Subject Haut-Rhin E49743 entity
Predicate contains P35 FINISHED
Object Thann
Thann is a small historic town in northeastern France, located at the foot of the Vosges mountains in the Haut-Rhin department of Alsace.
 E246529 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: Thann | Statement: [Haut-Rhin, contains, Thann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Thann
Context triple: [Haut-Rhin, contains, Thann]
  • A. Tynaarlo
    Tynaarlo is a municipality in the northeastern Netherlands known for its rural character and location between the cities of Groningen and Assen.
  • B. Tura
    Tura is a prominent town in the Indian state of Meghalaya, serving as a major administrative, cultural, and economic center in the Garo Hills region.
  • C. Tura
    Tura is a district in southern Cairo, Egypt, historically known for its limestone quarries used in ancient Egyptian monuments.
  • D. Krakhuna
    Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
  • E. Liluah
    Liluah is a suburban locality in the Howrah district of West Bengal, India, known for its residential areas and railway facilities near Kolkata.
  • 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: Thann
Triple: [Haut-Rhin, contains, Thann]
Generated description
Thann is a small historic town in northeastern France, located at the foot of the Vosges mountains in the Haut-Rhin department of Alsace.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Thann
Target entity description: Thann is a small historic town in northeastern France, located at the foot of the Vosges mountains in the Haut-Rhin department of Alsace.
  • A. Tynaarlo
    Tynaarlo is a municipality in the northeastern Netherlands known for its rural character and location between the cities of Groningen and Assen.
  • B. Tura
    Tura is a prominent town in the Indian state of Meghalaya, serving as a major administrative, cultural, and economic center in the Garo Hills region.
  • C. Tura
    Tura is a district in southern Cairo, Egypt, historically known for its limestone quarries used in ancient Egyptian monuments.
  • D. Krakhuna
    Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
  • E. Liluah
    Liluah is a suburban locality in the Howrah district of West Bengal, India, known for its residential areas and railway facilities near Kolkata.
  • 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_69a88aaa9250819095e127d0d77e8a32 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc1570dc88190bb2b17ed4c25dbb5 completed March 7, 2026, 6:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6b2229288190a7da9025dc394e67 completed March 9, 2026, 6:39 a.m.
NEDg Description generation batch_69ae6b5814f88190b6ff9d586d2b6351 completed March 9, 2026, 6:40 a.m.
NED2 Entity disambiguation (via description) batch_69ae6befcf4081909e1ee5d18abea357 completed March 9, 2026, 6:42 a.m.
Created at: March 4, 2026, 7:47 p.m.