Triple
T29128474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North West Victoria wine zone |
E738299
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object |
Australian wine industry
The Australian wine industry is a major global wine producer encompassing diverse wine regions across the country, known for varieties such as Shiraz, Cabernet Sauvignon, and Chardonnay.
|
E1850410
|
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: Australian wine industry | Statement: [North West Victoria wine zone, partOf, Australian wine industry]
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: Australian wine industry Triple: [North West Victoria wine zone, partOf, Australian wine industry]
Generated description
The Australian wine industry is a major global wine producer encompassing diverse wine regions across the country, known for varieties such as Shiraz, Cabernet Sauvignon, and Chardonnay.
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_69f07cb29cdc8190afa55444553de60c |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6622c2e1c819093b43ecb65f3fa52 |
completed | May 2, 2026, 8:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2537d1e3548190b843150dfd2a622a |
completed | June 7, 2026, 9:20 a.m. |
| NEDg | Description generation | batch_6a253bbd62288190b2cc1a79051748a7 |
completed | June 7, 2026, 9:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a253f918e1081909cc569d20fa9bf35 |
completed | June 7, 2026, 9:53 a.m. |
Created at: April 28, 2026, 11:30 a.m.