Triple
T22516794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strongbow Original |
E556668
|
entity |
| Predicate | hasParentBrand |
P6092
|
FINISHED |
| Object | Strongbow |
—
|
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: Strongbow | Statement: [Strongbow Original, hasParentBrand, Strongbow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Strongbow Context triple: [Strongbow Original, hasParentBrand, Strongbow]
-
A.
Strongbow
Strongbow was the nickname of Richard de Clare, a 12th-century Anglo-Norman nobleman famed for leading the Norman invasion of Ireland.
-
B.
Strongbow
chosen
Strongbow is a popular global cider brand best known for its crisp, dry apple cider produced by H. P. Bulmer in the United Kingdom.
-
C.
Strongbow Original
Strongbow Original is a flagship dry apple cider known for its crisp, refreshing taste and wide availability in pubs and stores.
-
D.
Strongbow Dark Fruit
Strongbow Dark Fruit is a popular fruit-flavoured cider known for its sweet, berry-forward taste and deep, dark colour.
-
E.
Boddington
Boddington is a small rural town in Western Australia known for its mining industry and agricultural surroundings.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e5657e881909f16ca58352c50da |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15e2df59c81909c4ae2f20f1cbb32 |
completed | April 29, 2026, 1:26 a.m. |
Created at: April 16, 2026, 8:50 p.m.