Triple
T14216870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Hoar |
E352375
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Silk |
E506423
|
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: Silk | Statement: [Peter Hoar, notableWork, Silk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Silk Context triple: [Peter Hoar, notableWork, Silk]
-
A.
Silk
chosen
Silk is a British legal drama television series centered on the personal and professional lives of barristers in London.
-
B.
Silk
Silk is a popular plant-based food and beverage brand known for its soy, almond, oat, and other non-dairy milk alternatives.
-
C.
Silk
Silk is an American R&B group best known for their smooth harmonies and 1990s slow jams like the hit single "Freak Me."
-
D.
Silk
Silk is a surname of English origin borne by various individuals, including American ice hockey player Dave Silk.
-
E.
Silken Floss
Silken Floss is a stylish and enigmatic femme fatale and scientist who serves as one of the main villains in the 2008 superhero film "The Spirit."
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6210213481908fac6893e8a9f143 |
completed | April 14, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd28101e1881909f7a6c0cc762204c |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 10, 2026, 1:06 a.m.