Triple

T12055692
Position Surface form Disambiguated ID Type / Status
Subject Grabs E287035 entity
Predicate hasSettlement P1068 FINISHED
Object Studen
Studen is a municipality in the canton of Bern in Switzerland, known for its residential character and proximity to the city of Biel/Bienne.
 E962009 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: Studen | Statement: [Grabs, hasSettlement, Studen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Studen
Context triple: [Grabs, hasSettlement, Studen]
  • A. Estudiantes
    Estudiantes is the nickname of Tecos F.C., a Mexican football club historically associated with the Universidad Autónoma de Guadalajara.
  • B. The Student
    The Student is a fictional character in Henry Wadsworth Longfellow’s narrative poem collection "Tales of a Wayside Inn," representing one of the storytellers gathered at the inn.
  • C. Student
    Student is a common surname that can be held by individuals such as Kurt Student, a notable historical figure.
  • D. STU
    STU is a major public technical university in Bratislava, Slovakia, known for its engineering, technology, and applied science programs.
  • E. Stu
    Stu is the nickname of Stuart A. Roosa, the American astronaut who served as Command Module Pilot on the Apollo 14 mission to the Moon.
  • 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: Studen
Triple: [Grabs, hasSettlement, Studen]
Generated description
Studen is a municipality in the canton of Bern in Switzerland, known for its residential character and proximity to the city of Biel/Bienne.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Studen
Target entity description: Studen is a municipality in the canton of Bern in Switzerland, known for its residential character and proximity to the city of Biel/Bienne.
  • A. Estudiantes
    Estudiantes is the nickname of Tecos F.C., a Mexican football club historically associated with the Universidad Autónoma de Guadalajara.
  • B. The Student
    The Student is a fictional character in Henry Wadsworth Longfellow’s narrative poem collection "Tales of a Wayside Inn," representing one of the storytellers gathered at the inn.
  • C. Student
    Student is a common surname that can be held by individuals such as Kurt Student, a notable historical figure.
  • D. STU
    STU is a major public technical university in Bratislava, Slovakia, known for its engineering, technology, and applied science programs.
  • E. Stu
    Stu is the nickname of Stuart A. Roosa, the American astronaut who served as Command Module Pilot on the Apollo 14 mission to the Moon.
  • 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_69d6ab4780948190bdb9f7620c2ac27e completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90425258c8190ba7b3b837c439253 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49dea043c8190a74ffb448bbae5d0 completed May 1, 2026, 12:34 p.m.
NEDg Description generation batch_69f53d96c3f08190847ba49929b7628f completed May 1, 2026, 11:56 p.m.
NED2 Entity disambiguation (via description) batch_69f564d2b4348190abf2d09ae00aea37 completed May 2, 2026, 2:43 a.m.
Created at: April 8, 2026, 9:47 p.m.