Triple

T28558677
Position Surface form Disambiguated ID Type / Status
Subject Oberer Schlossgarten E723073 entity
Predicate nameMeaning P453 FINISHED
Object Upper Palace Garden
Upper Palace Garden is a historic landscaped park area in Stuttgart, Germany, known for its green spaces, walking paths, and proximity to the city’s palace complex.
E1822565 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: Upper Palace Garden | Statement: [Oberer Schlossgarten, nameMeaning, Upper Palace Garden]
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: Upper Palace Garden
Triple: [Oberer Schlossgarten, nameMeaning, Upper Palace Garden]
Generated description
Upper Palace Garden is a historic landscaped park area in Stuttgart, Germany, known for its green spaces, walking paths, and proximity to the city’s palace complex.

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_69f01a60204481909af1bb76247b8221 completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f6505193988190b1e7879009d997ef completed May 2, 2026, 7:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cac73518c819096cac0c05a47eecd completed May 31, 2026, 9:47 p.m.
NEDg Description generation batch_6a1cad2176088190b0a526811f5c0016 completed May 31, 2026, 9:50 p.m.
NED2 Entity disambiguation (via description) batch_6a1cadfcbe9481909de0ae4896d34859 completed May 31, 2026, 9:54 p.m.
Created at: April 28, 2026, 3:47 a.m.