Triple

T31962508
Position Surface form Disambiguated ID Type / Status
Subject Schleswig harbor E816079 entity
Predicate locatedInMunicipality P40 FINISHED
Object Stadt Schleswig
Stadt Schleswig is a historic town in northern Germany’s Schleswig-Holstein region, known for its location on the Schlei inlet and its maritime and cultural heritage.
E1990737 NE FINISHED

How this triple was built (2 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: Stadt Schleswig | Statement: [Schleswig harbor, locatedInMunicipality, Stadt Schleswig]
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: Stadt Schleswig
Triple: [Schleswig harbor, locatedInMunicipality, Stadt Schleswig]
Generated description
Stadt Schleswig is a historic town in northern Germany’s Schleswig-Holstein region, known for its location on the Schlei inlet and its maritime and cultural heritage.

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_69f348f4ec708190abbb2a7c3ed58844 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b2e818e4819088fc7699503d4242 completed May 3, 2026, 2:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2eddcf3e7c8190a5a30c44ca30d968 completed June 14, 2026, 4:58 p.m.
NEDg Description generation batch_6a2edea2a2e8819087f7ba8685391436 completed June 14, 2026, 5:02 p.m.
NED2 Entity disambiguation (via description) batch_6a2edf61f11081909a3eb6468d916240 completed June 14, 2026, 5:05 p.m.
Created at: May 1, 2026, 12:09 a.m.