Triple
T20232484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Talons of Weng-Chiang |
E495561
|
entity |
| Predicate | influencedBy |
P9
|
FINISHED |
| Object | Sherlock Holmes |
—
|
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: Sherlock Holmes | Statement: [The Talons of Weng-Chiang, influencedBy, Sherlock Holmes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sherlock Holmes Context triple: [The Talons of Weng-Chiang, influencedBy, Sherlock Holmes]
-
A.
Hugh Sherlock
Hugh Sherlock was a Jamaican clergyman, social worker, and poet best known for writing the lyrics of Jamaica’s national anthem.
-
B.
Jerry Sherlock
Jerry Sherlock was a film producer best known for producing the 1990 submarine thriller "The Hunt for Red October."
-
C.
Holmes
chosen
Holmes is a common English surname borne by numerous notable figures, including writers, jurists, and fictional characters such as Sherlock Holmes.
-
D.
Holmes
Holmes is a consumer brand best known for its home comfort products such as fans, heaters, and air purifiers.
-
E.
Dr. Watson
Dr. Watson is the loyal friend, assistant, and biographer of Sherlock Holmes in Arthur Conan Doyle’s detective stories.
- 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e67166d4d081908c4b8eeb66e7e090 |
completed | April 20, 2026, 6:33 p.m. |
Created at: April 11, 2026, 11:40 p.m.