Triple
T36978502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pilot V Razor Point |
E914759
|
entity |
| Predicate | writingQuality |
P173939
|
FINISHED |
| Object | smooth |
—
|
LITERAL 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: smooth | Statement: [Pilot V Razor Point, writingQuality, smooth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writingQuality Context triple: [Pilot V Razor Point, writingQuality, smooth]
-
A.
editingQuality
Indicates the degree to which an editing action or process meets standards of accuracy, clarity, and effectiveness.
-
B.
stylisticQuality
chosen
Indicates the relationship in which one entity characterizes or evaluates the manner, style, or expressive quality of another entity or work.
-
C.
qualityInFiction
Indicates that a particular quality, trait, or characteristic is exhibited by an entity within a fictional context or work.
-
D.
writingModel
Indicates that one entity serves as the writing system, script, or notation model used to represent the language or written content of another entity.
-
E.
writingSampleScored
Indicates that a writing sample has been evaluated and assigned a score or rating.
- F. None of above.
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_69f76e8d13b4819089af24a47ce092fc |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:14 p.m.