Triple

T22631596
Position Surface form Disambiguated ID Type / Status
Subject Stockholm County lake system E558567 entity
Predicate hasPart P35 FINISHED
Object Lake Flaten
Lake Flaten is a freshwater lake in Stockholm County, Sweden, known for its clean waters, recreational beaches, and surrounding nature reserve popular for outdoor activities.
E1683943 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: Lake Flaten | Statement: [Stockholm County lake system, hasPart, Lake Flaten]
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: Lake Flaten
Triple: [Stockholm County lake system, hasPart, Lake Flaten]
Generated description
Lake Flaten is a freshwater lake in Stockholm County, Sweden, known for its clean waters, recreational beaches, and surrounding nature reserve popular for outdoor activities.

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_69e245467d9881908d6985bd0db7a1f1 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f17009ecb0819082f94505b0e2c5b8 completed April 29, 2026, 2:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10ad1b164c81909e374fa0b402f137 completed May 22, 2026, 7:23 p.m.
NEDg Description generation batch_6a10aeae38748190a970045e9bbd49f7 completed May 22, 2026, 7:29 p.m.
NED2 Entity disambiguation (via description) batch_6a10af62078481908759f9df2167d81f completed May 22, 2026, 7:32 p.m.
Created at: April 17, 2026, 3:02 p.m.