Triple

T35341243
Position Surface form Disambiguated ID Type / Status
Subject Książ Castle E1020601 entity
Predicate hasView P854 FINISHED
Object Chełmiec Massif
Chełmiec Massif is a prominent mountain massif in the Central Sudetes of southwestern Poland, known for its forested slopes, hiking trails, and panoramic views over the surrounding Wałbrzych region.
E2137802 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: Chełmiec Massif | Statement: [Książ Castle, hasView, Chełmiec Massif]
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: Chełmiec Massif
Triple: [Książ Castle, hasView, Chełmiec Massif]
Generated description
Chełmiec Massif is a prominent mountain massif in the Central Sudetes of southwestern Poland, known for its forested slopes, hiking trails, and panoramic views over the surrounding Wałbrzych region.

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_69f76debb4e08190be52d89b8af2392d completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f791592c5c819097f567dde258ac26 completed May 3, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3823cc7d38819085a1c9f453f8d7ff completed June 21, 2026, 5:47 p.m.
NEDg Description generation batch_6a3827b7d6148190a1902365ace9534c completed June 21, 2026, 6:04 p.m.
NED2 Entity disambiguation (via description) batch_6a3828189b6c8190839cbe2cb534368d completed June 21, 2026, 6:06 p.m.
Created at: May 3, 2026, 4:03 p.m.