Triple

T33842676

Position	Surface form	Disambiguated ID	Type / Status
Subject	Cadigal	`E867395`	entity
Predicate	hasAlternativeName	`P39`	FINISHED
Object	Cadigal people The Cadigal people are an Aboriginal Australian group traditionally associated with the area around present-day Sydney, particularly the southern side of Sydney Harbour.	`E2097935`	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: Cadigal people | Statement: [Cadigal, hasAlternativeName, Cadigal people]

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: Cadigal people
Triple: [Cadigal, hasAlternativeName, Cadigal people]

Generated description

The Cadigal people are an Aboriginal Australian group traditionally associated with the area around present-day Sydney, particularly the southern side of Sydney Harbour.

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_69f34992ad40819087760ed939bd2a7a`	completed	April 30, 2026, 12:22 p.m.
NER	Named-entity recognition	`batch_69f7005069dc8190a8473c015571a4a0`	completed	May 3, 2026, 7:59 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a3721151a8c8190a8fe8a1dbc25aaff`	completed	June 20, 2026, 11:24 p.m.
NEDg	Description generation	`batch_6a3721be9f4881908ebee1b76d4ff59f`	completed	June 20, 2026, 11:26 p.m.
NED2	Entity disambiguation (via description)	`batch_6a37224447088190abded9d7634e4766`	completed	June 20, 2026, 11:29 p.m.

Created at: May 1, 2026, 1:47 a.m.