Triple
T1151171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heineken N.V. |
E23679
|
entity |
| Predicate | hasGlobalBrand |
P26115
|
FINISHED |
| Object | Amstel |
E137013
|
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: Amstel | Statement: [Heineken N.V., hasGlobalBrand, Amstel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amstel Context triple: [Heineken N.V., hasGlobalBrand, Amstel]
-
A.
Amsterdam Amstel
Amsterdam Amstel is a major railway and metro station in Amsterdam that serves as an important transport hub connecting regional and local lines.
-
B.
Amstel brand
chosen
Amstel brand is a Dutch beer brand best known for its lagers and international presence, produced under the ownership of Heineken.
-
C.
Heineken Experience brewery
The Heineken Experience brewery is a popular interactive museum and former brewery in Amsterdam dedicated to the history and brewing process of Heineken beer.
-
D.
Heineken lager beer
Heineken lager beer is a globally recognized pale lager known for its distinctive green bottle, red star logo, and crisp, mildly bitter taste.
-
E.
Heineken France
Heineken France is the French brewing and beverage subsidiary of the global Dutch beer company Heineken, responsible for producing, marketing, and distributing its brands in France.
- 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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bf13ab648190931dea78202096e4 |
completed | March 1, 2026, 10:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acacacf7c4819089708cf61b89903c |
completed | March 7, 2026, 10:54 p.m. |
Created at: March 1, 2026, 7:44 p.m.