Triple

T9263084
Position Surface form Disambiguated ID Type / Status
Subject German Fairy Tale Route E222625 entity
Predicate passesThrough P225 FINISHED
Object Trendelburg
Trendelburg is a small historic town in northern Hesse, Germany, best known for its medieval castle and association with the Rapunzel fairy tale.
E789999 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: Trendelburg | Statement: [German Fairy Tale Route, passesThrough, Trendelburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trendelburg
Context triple: [German Fairy Tale Route, passesThrough, Trendelburg]
  • A. Neuhof
    Neuhof is a district (Ortsteil) of the town of Taunusstein in the Rheingau-Taunus-Kreis region of Hesse, Germany.
  • B. Eschwege
    Eschwege is a small historic town in the German state of Hesse, known for its medieval architecture and location near the Werra River.
  • C. Euerbach
    Euerbach is a small municipality in the Schweinfurt district of northern Bavaria, Germany, known for its rural character and Franconian cultural heritage.
  • D. Vechigen
    Vechigen is a rural municipality in the canton of Bern, Switzerland, known for its scattered settlements and agricultural landscape near the city of Bern.
  • E. Tureberg
    Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
  • 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: Trendelburg
Triple: [German Fairy Tale Route, passesThrough, Trendelburg]
Generated description
Trendelburg is a small historic town in northern Hesse, Germany, best known for its medieval castle and association with the Rapunzel fairy tale.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Trendelburg
Target entity description: Trendelburg is a small historic town in northern Hesse, Germany, best known for its medieval castle and association with the Rapunzel fairy tale.
  • A. Neuhof
    Neuhof is a district (Ortsteil) of the town of Taunusstein in the Rheingau-Taunus-Kreis region of Hesse, Germany.
  • B. Eschwege
    Eschwege is a small historic town in the German state of Hesse, known for its medieval architecture and location near the Werra River.
  • C. Euerbach
    Euerbach is a small municipality in the Schweinfurt district of northern Bavaria, Germany, known for its rural character and Franconian cultural heritage.
  • D. Vechigen
    Vechigen is a rural municipality in the canton of Bern, Switzerland, known for its scattered settlements and agricultural landscape near the city of Bern.
  • E. Tureberg
    Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
  • 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_69ca841f2e808190a64f4c31903a1332 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd0719eee081909e21ecb9d6dd0b49 completed April 1, 2026, 11:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0b1e30c648190a2c6a8c4c6da390c completed April 4, 2026, 6:38 a.m.
NEDg Description generation batch_69d0b3ba0bd88190873816ec7e7929a7 completed April 4, 2026, 6:46 a.m.
NED2 Entity disambiguation (via description) batch_69d0b49ec4c88190a48909e7022d7e60 completed April 4, 2026, 6:50 a.m.
Created at: March 30, 2026, 7:32 p.m.