Triple

T18127920
Position Surface form Disambiguated ID Type / Status
Subject Weißenburg-Gunzenhausen district E433929 entity
Predicate containsMarketTown P130562 FINISHED
Object Heideck
Heideck is a small market town in the Weißenburg-Gunzenhausen district of Bavaria, Germany, known for its rural character and regional historical charm.
 E1308422 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: Heideck | Statement: [Weißenburg-Gunzenhausen district, containsMarketTown, Heideck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Heideck
Context triple: [Weißenburg-Gunzenhausen district, containsMarketTown, Heideck]
  • A. Heideck
    Heideck was a notable Philhellene, remembered for his support of the Greek cause during the Greek War of Independence.
  • B. Burgard
    Burgard is a German surname borne by individuals such as the computer scientist Wolfram Burgard.
  • C. Schlöndorff
    Schlöndorff is the surname of Volker Schlöndorff, a prominent German film director and screenwriter known for works such as "The Tin Drum."
  • D. Hauke
    Hauke is a Germanic given name, particularly common in Northern Germany, that is cognate with the English name Hugh.
  • E. Leiningen
    Leiningen is a popular build automation and project management tool for the Clojure programming language, used to manage dependencies, run tasks, and streamline development workflows.
  • 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: Heideck
Triple: [Weißenburg-Gunzenhausen district, containsMarketTown, Heideck]
Generated description
Heideck is a small market town in the Weißenburg-Gunzenhausen district of Bavaria, Germany, known for its rural character and regional historical charm.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Heideck
Target entity description: Heideck is a small market town in the Weißenburg-Gunzenhausen district of Bavaria, Germany, known for its rural character and regional historical charm.
  • A. Heideck
    Heideck was a notable Philhellene, remembered for his support of the Greek cause during the Greek War of Independence.
  • B. Burgard
    Burgard is a German surname borne by individuals such as the computer scientist Wolfram Burgard.
  • C. Schlöndorff
    Schlöndorff is the surname of Volker Schlöndorff, a prominent German film director and screenwriter known for works such as "The Tin Drum."
  • D. Hauke
    Hauke is a Germanic given name, particularly common in Northern Germany, that is cognate with the English name Hugh.
  • E. Leiningen
    Leiningen is a popular build automation and project management tool for the Clojure programming language, used to manage dependencies, run tasks, and streamline development workflows.
  • 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_69d8b909e8cc81908df4cc2b8ea6d11f completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ddef4cd88190b16ef0d6ed3968c6 completed April 19, 2026, 1:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a038543ec98819080e1bb3981634ecb completed May 12, 2026, 7:53 p.m.
NEDg Description generation batch_6a0389649bac8190bb5f189e562ab8c3 completed May 12, 2026, 8:11 p.m.
NED2 Entity disambiguation (via description) batch_6a0389eb3928819080b6d257698e662c completed May 12, 2026, 8:13 p.m.
Created at: April 10, 2026, 10:29 a.m.