Triple

T13414317
Position Surface form Disambiguated ID Type / Status
Subject Lütschine E313169 entity
Predicate hasPart P35 FINISHED
Object Schwarze Lütschine
Schwarze Lütschine is a mountain river in the Bernese Oberland region of Switzerland, known for flowing through the Lauterbrunnen Valley before joining the Weisse Lütschine.
E1039330 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: Schwarze Lütschine | Statement: [Lütschine, hasPart, Schwarze Lütschine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwarze Lütschine
Context triple: [Lütschine, hasPart, Schwarze Lütschine]
  • A. Schwarze Elster
    Schwarze Elster is a river in eastern Germany that flows through Saxony, Brandenburg, and Saxony-Anhalt before joining the Elbe.
  • B. Die Rothosen
    Die Rothosen is the traditional German football club Hamburger SV’s nickname, referring to the team’s iconic red shorts and kit colors.
  • C. Schlawe
    Schlawe is a historic town in Pomerania, formerly in Prussia and now known as Sławno in northwestern Poland.
  • D. Blumenstück
    Blumenstück is a lyrical piano piece in D-flat major, Op. 19, by Robert Schumann, noted for its delicate, song-like character.
  • E. Waidmannslust
    Waidmannslust is a residential locality in the Reinickendorf borough of Berlin, Germany, known for its green spaces and suburban character.
  • 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: Schwarze Lütschine
Triple: [Lütschine, hasPart, Schwarze Lütschine]
Generated description
Schwarze Lütschine is a mountain river in the Bernese Oberland region of Switzerland, known for flowing through the Lauterbrunnen Valley before joining the Weisse Lütschine.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Schwarze Lütschine
Target entity description: Schwarze Lütschine is a mountain river in the Bernese Oberland region of Switzerland, known for flowing through the Lauterbrunnen Valley before joining the Weisse Lütschine.
  • A. Schwarze Elster
    Schwarze Elster is a river in eastern Germany that flows through Saxony, Brandenburg, and Saxony-Anhalt before joining the Elbe.
  • B. Die Rothosen
    Die Rothosen is the traditional German football club Hamburger SV’s nickname, referring to the team’s iconic red shorts and kit colors.
  • C. Schlawe
    Schlawe is a historic town in Pomerania, formerly in Prussia and now known as Sławno in northwestern Poland.
  • D. Blumenstück
    Blumenstück is a lyrical piano piece in D-flat major, Op. 19, by Robert Schumann, noted for its delicate, song-like character.
  • E. Waidmannslust
    Waidmannslust is a residential locality in the Reinickendorf borough of Berlin, Germany, known for its green spaces and suburban character.
  • 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_69d806ad0c44819088833ae1ec9e9690 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaeb556948190af008c88e5bbf051 completed April 12, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7308095548190afb659b84f2775f2 completed May 3, 2026, 11:24 a.m.
NEDg Description generation batch_69f73242a368819080ceda37583c0d7c completed May 3, 2026, 11:32 a.m.
NED2 Entity disambiguation (via description) batch_69f732b3ba748190b2a430300e798ed8 completed May 3, 2026, 11:34 a.m.
Created at: April 9, 2026, 9:39 p.m.