Triple

T24954094
Position Surface form Disambiguated ID Type / Status
Subject McRae E624418 entity
Predicate hasNotableBearer P458 FINISHED
Object Tommy McRae
Tommy McRae was a renowned 19th-century Aboriginal Australian artist known for his detailed pen-and-ink drawings depicting Indigenous life and colonial encounters.
E888467 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: Tommy McRae | Statement: [McRae, hasNotableBearer, Tommy McRae]
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: Tommy McRae
Triple: [McRae, hasNotableBearer, Tommy McRae]
Generated description
Tommy McRae was a renowned 19th-century Aboriginal Australian artist known for his detailed pen-and-ink drawings depicting Indigenous life and colonial encounters.

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_69e2ff23a3a88190b1b9743fe5e15f94 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f4240239e88190aa04201eb7d8a80b completed May 1, 2026, 3:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10334e44748190a6342b9888ee76d5 completed May 22, 2026, 10:43 a.m.
NEDg Description generation batch_6a103420ed908190b7be8e1a8b82a85c completed May 22, 2026, 10:46 a.m.
NED2 Entity disambiguation (via description) batch_6a1034aa0ed881909d877e1d9159b9d2 completed May 22, 2026, 10:49 a.m.
Created at: April 18, 2026, 5:57 a.m.