Triple
T7113392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L&M |
E165756
|
entity |
| Predicate | hasCompetitor |
P1375
|
FINISHED |
| Object | Winston |
E47182
|
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: Winston | Statement: [L&M, hasCompetitor, Winston]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Winston Context triple: [L&M, hasCompetitor, Winston]
-
A.
Winston
chosen
Winston is a long-established American cigarette brand known for its filtered cigarettes and prominent mid-20th-century advertising campaigns.
-
B.
Winston
Winston is the given name of Winston Churchill, the British statesman who led the United Kingdom during World War II and later served again as Prime Minister.
-
C.
Winston
Winston is a supporting character in the dark comedy film "Sunshine Cleaning," involved in the story of two sisters who start a crime-scene cleanup business.
-
D.
Winston
Winston is a suave and enigmatic crime lord who manages the Continental Hotel in the John Wick film series.
-
E.
Winston
Winston is a character in the film "Broken Flowers," known as Don Johnston’s enthusiastic, mystery-loving neighbor who pushes him to investigate his past relationships.
- 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_69c6888120f081908f8f01b201dc4a4c |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e5ef813c8190bec0ab0cbae430e5 |
completed | March 27, 2026, 8:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79cbc35d48190974e207eb98dcbe3 |
completed | March 28, 2026, 9:17 a.m. |
Created at: March 27, 2026, 2:43 p.m.