Triple

T38016959
Position Surface form Disambiguated ID Type / Status
Subject Australian Communications Authority E948522 entity
Predicate hasAbbreviation P43 FINISHED
Object ACA
ACA is the abbreviation for the Australian Communications Authority, the former Australian government regulator responsible for telecommunications and radiocommunications.
E2253730 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: ACA | Statement: [Australian Communications Authority, hasAbbreviation, ACA]
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: ACA
Triple: [Australian Communications Authority, hasAbbreviation, ACA]
Generated description
ACA is the abbreviation for the Australian Communications Authority, the former Australian government regulator responsible for telecommunications and radiocommunications.

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_69f76efc10448190aff5fb566b98f952 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbc96cbe448190a94ccbc791e903c3 completed May 6, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41543764f88190a53a9f985ea67d4f completed June 28, 2026, 5:04 p.m.
NEDg Description generation batch_6a41564311288190ad9b0507208d42aa completed June 28, 2026, 5:13 p.m.
NED2 Entity disambiguation (via description) batch_6a4156d3f78c8190a47fefb7ad24b221 completed June 28, 2026, 5:16 p.m.
Created at: May 3, 2026, 4:20 p.m.