Triple

T27625385
Position Surface form Disambiguated ID Type / Status
Subject Forestville E696188 entity
Predicate hasReligiousBuilding P1191 FINISHED
Object Forestville Uniting Church
Forestville Uniting Church is a Christian congregation and worship centre serving the local community of Forestville, Australia.
E1780126 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: Forestville Uniting Church | Statement: [Forestville, hasReligiousBuilding, Forestville Uniting Church]
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: Forestville Uniting Church
Triple: [Forestville, hasReligiousBuilding, Forestville Uniting Church]
Generated description
Forestville Uniting Church is a Christian congregation and worship centre serving the local community of Forestville, Australia.

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_69ef59092c8881908114ad184248cc46 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f6311f4dc48190a88ba7863642a3e6 completed May 2, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12d0f73a508190b818eaf903620ac7 completed May 24, 2026, 10:20 a.m.
NEDg Description generation batch_6a12d1b7236c819092446204ac71c8b2 completed May 24, 2026, 10:23 a.m.
NED2 Entity disambiguation (via description) batch_6a12d26af1288190a2925d726ab5be31 completed May 24, 2026, 10:26 a.m.
Created at: April 27, 2026, 2:17 p.m.