Triple

T24903710
Position Surface form Disambiguated ID Type / Status
Subject City of Port Phillip E623647 entity
Predicate contains P35 FINISHED
Object Veg Out Community Garden
Veg Out Community Garden is a volunteer-run, urban community garden in the City of Port Phillip that provides shared plots, green space, and educational activities for local residents.
E1658824 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: Veg Out Community Garden | Statement: [City of Port Phillip, contains, Veg Out Community 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: Veg Out Community Garden
Triple: [City of Port Phillip, contains, Veg Out Community Garden]
Generated description
Veg Out Community Garden is a volunteer-run, urban community garden in the City of Port Phillip that provides shared plots, green space, and educational activities for local residents.

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_69e2fac797cc8190b30d77f4121099ac completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f42369fb3c8190861f8955a34ac04b completed May 1, 2026, 3:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1033263a58819087885c25e94299bf completed May 22, 2026, 10:42 a.m.
NEDg Description generation batch_6a10341f2f84819080ce00e1d48f4fa1 completed May 22, 2026, 10:46 a.m.
NED2 Entity disambiguation (via description) batch_6a1035247f388190ab632ce2036efd8c completed May 22, 2026, 10:51 a.m.
Created at: April 18, 2026, 5:27 a.m.