Triple
T27050966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | YouTube Symphony Orchestra |
E684770
|
entity |
| Predicate | countryOfSecondMajorEvent |
P42769
|
FINISHED |
| Object | Australia |
—
|
NE NERFINISHED |
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: Australia | Statement: [YouTube Symphony Orchestra, countryOfSecondMajorEvent, Australia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfSecondMajorEvent Context triple: [YouTube Symphony Orchestra, countryOfSecondMajorEvent, Australia]
-
A.
cityOfSecondMajorEvent
Indicates the city where the second major event in a sequence or series takes place.
-
B.
countryWithMultipleEvents
Indicates that a country is associated with more than one event within the given context or dataset.
-
C.
majorEventCountry
Indicates that a major event took place in, or is primarily associated with, a particular country.
-
D.
countryWhereOccurred
chosen
Indicates the country in which a particular event, action, or occurrence took place.
-
E.
countryOfFirstEvent
Indicates the country in which the first event in a sequence or series took place.
- F. None of above.
Provenance (3 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_69ef14829fac8190914bef9ecc3005d7 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: April 27, 2026, 8:14 a.m.