Triple

T38095015
Position Surface form Disambiguated ID Type / Status
Subject Purkersdorf (Lower Austria) E951219 entity
Predicate hasGreenSpace P1495 FINISHED
Object Purkersdorf Forest
Purkersdorf Forest is a protected woodland and recreational area near Purkersdorf in Lower Austria, known for its natural habitats and outdoor leisure opportunities.
E2257006 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: Purkersdorf Forest | Statement: [Purkersdorf (Lower Austria), hasGreenSpace, Purkersdorf Forest]
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: Purkersdorf Forest
Triple: [Purkersdorf (Lower Austria), hasGreenSpace, Purkersdorf Forest]
Generated description
Purkersdorf Forest is a protected woodland and recreational area near Purkersdorf in Lower Austria, known for its natural habitats and outdoor leisure opportunities.

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_69f76f04960c8190a83f14ae4c67f5bc completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc458abc7c819099a0d0a3f05c6285 completed May 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a41680c11748190b11a90beff8017f8 completed June 28, 2026, 6:29 p.m.
NEDg Description generation batch_6a416bdd755c8190951cb9fa84a487a0 completed June 28, 2026, 6:45 p.m.
NED2 Entity disambiguation (via description) batch_6a416cd609088190b91e9b633fe67918 completed June 28, 2026, 6:49 p.m.
Created at: May 3, 2026, 4:21 p.m.