Triple
T23200266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Associated British Foods |
E579986
|
entity |
| Predicate | parentCompanyOf |
P254
|
FINISHED |
| Object | Twinings |
—
|
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: Twinings | Statement: [Associated British Foods, parentCompanyOf, Twinings]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Twinings Context triple: [Associated British Foods, parentCompanyOf, Twinings]
-
A.
Twinings
chosen
Twinings is a historic British tea company renowned worldwide for its wide range of premium teas and herbal infusions.
-
B.
Lipton
Lipton is a globally recognized tea brand offering a wide range of tea products, including black, green, and herbal varieties.
-
C.
Tata Tea
Tata Tea is a major Indian tea brand and beverage company, part of the Tata Group, known for its wide range of packaged teas and strong presence in the domestic and international markets.
-
D.
Teavana
Teavana is a specialty tea retailer and brand known for its loose-leaf teas, tea accessories, and tea-centric beverages.
-
E.
Tunnock's
Tunnock's is a famous Scottish confectionery company best known for its caramel wafers and teacakes.
- 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_69e24600eed08190bd7e5295653a1503 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f19078f28c8190973f1bd6f2bceb5a |
completed | April 29, 2026, 5 a.m. |
Created at: April 17, 2026, 4:06 p.m.