Triple
T11027772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cinemastar |
E260672
|
entity |
| Predicate | relatedProductLine |
P37
|
FINISHED |
| Object | Deskstar |
E260671
|
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: Deskstar | Statement: [Cinemastar, relatedProductLine, Deskstar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Deskstar Context triple: [Cinemastar, relatedProductLine, Deskstar]
-
A.
Deskstar
chosen
Deskstar is a line of hard disk drives originally produced under the Hitachi Global Storage Technologies (HGST) brand, known for desktop data storage.
-
B.
Eazel
Eazel was a short-lived software company best known for developing the Nautilus file manager and attempting to simplify the Linux desktop experience around 2000–2001.
-
C.
Turbostar
Turbostar is a family of modern British diesel multiple-unit trains widely used for regional and commuter services across the UK rail network.
-
D.
Stello
Stello is the surname of Dick Stello, a former Major League Baseball umpire known for his work in the National League.
-
E.
Wyse
Wyse is an alternative spelling of the surname Wise, which is borne by various individuals and businesses.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797d190f08190bcb5949ee24306f1 |
completed | April 9, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3753451e08190bc42ab99d01926f9 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 8, 2026, 9:25 p.m.