Triple
T5253165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rupert Penry-Jones |
E118635
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Silk
Silk is a British legal drama television series centered on the personal and professional lives of barristers in London.
|
E506423
|
NE FINISHED |
How this triple was built (4 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: [Rupert Penry-Jones, notableWork, Silk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Silk Context triple: [Rupert Penry-Jones, notableWork, Silk]
-
A.
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."
-
B.
Cotten
Cotten is a surname most notably associated with American actor Joseph Cotten, a prominent figure in classic Hollywood cinema.
-
C.
Pashmina shawls
Pashmina shawls are luxurious, finely woven woolen wraps traditionally handcrafted from the soft undercoat of Himalayan goats, renowned for their exceptional warmth, lightness, and elegance.
-
D.
Cotton Tufts
Cotton Tufts was an 18th-century American physician and patriot from Massachusetts who was active in public affairs during the Revolutionary era.
-
E.
Cotton
Cotton is a soft, natural fiber harvested from the seed pods of cotton plants and widely used in textiles and clothing.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Silk Triple: [Rupert Penry-Jones, notableWork, Silk]
Generated description
Silk is a British legal drama television series centered on the personal and professional lives of barristers in London.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Silk Target entity description: Silk is a British legal drama television series centered on the personal and professional lives of barristers in London.
-
A.
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."
-
B.
Cotten
Cotten is a surname most notably associated with American actor Joseph Cotten, a prominent figure in classic Hollywood cinema.
-
C.
Pashmina shawls
Pashmina shawls are luxurious, finely woven woolen wraps traditionally handcrafted from the soft undercoat of Himalayan goats, renowned for their exceptional warmth, lightness, and elegance.
-
D.
Cotton Tufts
Cotton Tufts was an 18th-century American physician and patriot from Massachusetts who was active in public affairs during the Revolutionary era.
-
E.
Cotton
Cotton is a soft, natural fiber harvested from the seed pods of cotton plants and widely used in textiles and clothing.
- F. None of above. chosen
Provenance (5 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_69bd446978108190bb5f9c5c23d93f88 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b7cd7f4819098e591df07564a52 |
completed | March 20, 2026, 4:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69befe72c91c8190ab0f988dca420399 |
completed | March 21, 2026, 8:24 p.m. |
| NEDg | Description generation | batch_69beff668dbc8190bc71c8dae2b5ca72 |
completed | March 21, 2026, 8:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf00120fe88190817badb72977566e |
completed | March 21, 2026, 8:31 p.m. |
Created at: March 20, 2026, 1:50 p.m.