Triple

T24159316
Position Surface form Disambiguated ID Type / Status
Subject Königs Wusterhausen E598785 entity
Predicate hasLandmark P105 FINISHED
Object Old Town Hall of Königs Wusterhausen
The Old Town Hall of Königs Wusterhausen is a historic municipal building that once served as the town’s administrative center and now stands as a notable architectural and cultural landmark.
E1621337 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: Old Town Hall of Königs Wusterhausen | Statement: [Königs Wusterhausen, hasLandmark, Old Town Hall of Königs Wusterhausen]
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: Old Town Hall of Königs Wusterhausen
Triple: [Königs Wusterhausen, hasLandmark, Old Town Hall of Königs Wusterhausen]
Generated description
The Old Town Hall of Königs Wusterhausen is a historic municipal building that once served as the town’s administrative center and now stands as a notable architectural and cultural landmark.

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_69e288cb0a3081909ef221744f274384 completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1e0e7f8e481909c55ae66bf7b16e9 completed April 29, 2026, 10:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fad33825c81909fa6f19be6d18ece completed May 22, 2026, 1:11 a.m.
NEDg Description generation batch_6a0fae2d71448190b191a4877c698840 completed May 22, 2026, 1:15 a.m.
NED2 Entity disambiguation (via description) batch_6a0faf073c088190bbf21e4dd0434fc1 completed May 22, 2026, 1:19 a.m.
Created at: April 17, 2026, 11:32 p.m.