Triple
T9195271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Rendall |
E220689
|
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: [Mark Rendall, notableWork, Silk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Silk Context triple: [Mark Rendall, 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.
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.
Сатин
Сатин — один из центральных персонажей пьесы Максима Горького «На дне», философствующий босяк, чьи циничные, но проникновенные монологи выражают ключевые идеи произведения о правде и человеческом достоинстве.
- 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_69ca83e7ba70819088b74866d9da2c30 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd87c3a3c8190b60f19873ef6e1f8 |
completed | April 1, 2026, 8:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05c36d7208190a593923bad3d18e7 |
completed | April 4, 2026, 12:32 a.m. |
Created at: March 30, 2026, 7:25 p.m.