Triple

T30006160
Position Surface form Disambiguated ID Type / Status
Subject York, Western Australia E762325 entity
Predicate hasLandmark P105 FINISHED
Object Mount Brown lookout
Mount Brown lookout is a scenic vantage point near York in Western Australia, offering panoramic views of the surrounding countryside and town.
 E1894535 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: Mount Brown lookout | Statement: [York, Western Australia, hasLandmark, Mount Brown lookout]
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: Mount Brown lookout
Triple: [York, Western Australia, hasLandmark, Mount Brown lookout]
Generated description
Mount Brown lookout is a scenic vantage point near York in Western Australia, offering panoramic views of the surrounding countryside and town.

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_69f2246a47ac81909cf5213053687ffc completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6795282648190a8351e4cbace98d3 completed May 2, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27220ce5d081909ad93019664d334a completed June 8, 2026, 8:11 p.m.
NEDg Description generation batch_6a272333f384819084456b384bc17a6c completed June 8, 2026, 8:16 p.m.
NED2 Entity disambiguation (via description) batch_6a2723e6c6648190801fec9c9fd7f557 completed June 8, 2026, 8:19 p.m.
Created at: April 29, 2026, 6:42 p.m.