Triple
T11352519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DaVinci Resolve |
E268868
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object |
Cut page
Cut page is a streamlined, fast-paced editing workspace in DaVinci Resolve designed for quick assembly and trimming of video projects.
|
E920761
|
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: Cut page | Statement: [DaVinci Resolve, hasComponent, Cut page]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cut page Context triple: [DaVinci Resolve, hasComponent, Cut page]
-
A.
CUT
CUT is the National Rail station code assigned to Cutty Sark DLR station in London.
-
B.
CUT
CUT is the commonly used acronym for the Central University of Technology, a higher education institution in South Africa.
-
C.
CUT
CUT is a public university in Limassol, Cyprus, known for its focus on applied research and technology-oriented academic programs.
-
D.
Scissors Cut
Scissors Cut is a 1981 solo studio album by American singer Art Garfunkel, featuring soft rock and adult contemporary songs marked by his distinctive vocal style.
-
E.
Cut Piece
Cut Piece is a pioneering 1964 performance art work by Yoko Ono in which audience members were invited to cut away pieces of her clothing, exploring themes of vulnerability, participation, and aggression.
- 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: Cut page Triple: [DaVinci Resolve, hasComponent, Cut page]
Generated description
Cut page is a streamlined, fast-paced editing workspace in DaVinci Resolve designed for quick assembly and trimming of video projects.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cut page Target entity description: Cut page is a streamlined, fast-paced editing workspace in DaVinci Resolve designed for quick assembly and trimming of video projects.
-
A.
CUT
CUT is the National Rail station code assigned to Cutty Sark DLR station in London.
-
B.
CUT
CUT is the commonly used acronym for the Central University of Technology, a higher education institution in South Africa.
-
C.
CUT
CUT is a public university in Limassol, Cyprus, known for its focus on applied research and technology-oriented academic programs.
-
D.
Scissors Cut
Scissors Cut is a 1981 solo studio album by American singer Art Garfunkel, featuring soft rock and adult contemporary songs marked by his distinctive vocal style.
-
E.
Cut Piece
Cut Piece is a pioneering 1964 performance art work by Yoko Ono in which audience members were invited to cut away pieces of her clothing, exploring themes of vulnerability, participation, and aggression.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea24489081908fbf47fd2e6d709c |
completed | April 9, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e543a6e97481909dc77a553b217b4d |
completed | April 19, 2026, 9:05 p.m. |
| NEDg | Description generation | batch_69e548bb7be4819093aeeaf0c048033e |
completed | April 19, 2026, 9:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e54efda820819092d6a94fa4fd21f0 |
completed | April 19, 2026, 9:54 p.m. |
Created at: April 8, 2026, 9:33 p.m.