Triple

T27129322
Position Surface form Disambiguated ID Type / Status
Subject Tamarama Beach E681520 entity
Predicate partOf P40 FINISHED
Object Sydney coastline
The Sydney coastline is a renowned stretch of oceanfront in New South Wales, Australia, featuring a series of iconic beaches, cliffs, and coastal walks along the Pacific Ocean.
E1757819 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: Sydney coastline | Statement: [Tamarama Beach, partOf, Sydney coastline]
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: Sydney coastline
Triple: [Tamarama Beach, partOf, Sydney coastline]
Generated description
The Sydney coastline is a renowned stretch of oceanfront in New South Wales, Australia, featuring a series of iconic beaches, cliffs, and coastal walks along the Pacific Ocean.

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_69eefacbcc2081909ebf00daa23f1981 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f62475c1f481908f71234cd4d7012b completed May 2, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12481b1ad081909031cb6a66815a0c completed May 24, 2026, 12:36 a.m.
NEDg Description generation batch_6a1248e698008190b4e1d77080b52fef completed May 24, 2026, 12:40 a.m.
NED2 Entity disambiguation (via description) batch_6a1249ec94e48190acbcd83ba6d923ea completed May 24, 2026, 12:44 a.m.
Created at: April 27, 2026, 9:03 a.m.