Triple

T25228396
Position Surface form Disambiguated ID Type / Status
Subject Thomas Mayne E632154 entity
Predicate developed P73 FINISHED
Object chocolate malted milk drink Milo
Milo is a popular chocolate and malt powdered beverage, often mixed with milk or water, known for its energy-boosting marketing and widespread consumption, especially in countries like Australia and across Asia and Africa.
E1671546 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: chocolate malted milk drink Milo | Statement: [Thomas Mayne, developed, chocolate malted milk drink Milo]
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: chocolate malted milk drink Milo
Triple: [Thomas Mayne, developed, chocolate malted milk drink Milo]
Generated description
Milo is a popular chocolate and malt powdered beverage, often mixed with milk or water, known for its energy-boosting marketing and widespread consumption, especially in countries like Australia and across Asia and Africa.

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_69e75a8e0f688190a7aebe9a4815e25b completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f47cc52f3c8190a2a17ba58e5ca43f completed May 1, 2026, 10:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1067dca0548190a8f9633adabaeaee completed May 22, 2026, 2:27 p.m.
NEDg Description generation batch_6a1069760058819089d45fe0d4f630b8 completed May 22, 2026, 2:34 p.m.
NED2 Entity disambiguation (via description) batch_6a106a12f4e08190a51c4cecf7a5de2a completed May 22, 2026, 2:37 p.m.
Created at: April 21, 2026, 1:04 p.m.