Triple
T1977563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woman Reading |
E42949
|
entity |
| Predicate | colorRole |
P60
|
FINISHED |
| Object | expressive |
—
|
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: expressive | Statement: [Woman Reading, colorRole, expressive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorRole Context triple: [Woman Reading, colorRole, expressive]
-
A.
displayRole
Indicates the role or position an entity holds in the context of how it is presented or shown in a display.
-
B.
colors
chosen
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
C.
definesRole
Indicates that one entity specifies or establishes the role, function, or position of another entity within a given context.
-
D.
identificationRole
Indicates that an entity serves as an identifier or plays a role in uniquely distinguishing or recognizing another entity.
-
E.
languageFamilyColor
Indicates that a language family is associated with a particular color, typically for visualization or categorization purposes.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb42ecde881909bc9132885d8d0bd |
completed | March 7, 2026, 5:14 a.m. |
| PD | Predicate disambiguation | batch_69abaff9a09c8190a81fa13f4b85bc79 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.