Triple
T7972383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | On Purpose |
E185355
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Beer |
E531764
|
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: Beer | Statement: [On Purpose, hasTrack, Beer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beer Context triple: [On Purpose, hasTrack, Beer]
-
A.
Beer
chosen
Beer is a picturesque coastal village in Devon, England, known for its historic fishing heritage, limestone cliffs, and scenic pebble beach.
-
B.
Beers
Beers is a small village in the Dutch province of North Brabant, known for its rural character and location within the municipality of Land van Cuijk.
-
C.
Ales
Ales is the given name of Ales Bialiatski, a prominent Belarusian human rights activist and Nobel Peace Prize laureate.
-
D.
Wein
Wein is a surname most notably associated with George Wein, the influential American jazz promoter and founder of major music festivals such as the Newport Jazz Festival.
-
E.
Beery
Beery is a surname most notably associated with the American acting family that includes character actor Noah Beery and his relatives.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca8297699481909b75a405f01e03af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3bd580dc819084be5b7963b6029c |
completed | March 31, 2026, 3:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe0b207ec8190a1a78e77a6bdb15e |
completed | March 31, 2026, 2:56 p.m. |
Created at: March 30, 2026, 5:13 p.m.