Triple
T8966772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keith Sweat |
E214154
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Silk |
E579754
|
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: [Keith Sweat, associatedAct, Silk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Silk Context triple: [Keith Sweat, associatedAct, Silk]
-
A.
Silk
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
chosen
Silk is an American R&B group best known for their smooth harmonies and 1990s slow jams like the hit single "Freak Me."
-
D.
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."
-
E.
Şile cloth
Şile cloth is a traditional, lightweight, handwoven cotton fabric from the Turkish town of Şile, valued for its breathable, slightly crinkled texture and use in summer clothing and textiles.
- 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_69ca839cd6008190a1546a701a56710c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc676389948190aa78fdf6a5ae74a5 |
completed | April 1, 2026, 12:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc95879c08190b0091548c8c00207 |
completed | April 3, 2026, 2:06 p.m. |
Created at: March 30, 2026, 7:01 p.m.