Triple
T11936750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Purple Tilt |
E284063
|
entity |
| Predicate | hasTextProperty |
P62426
|
FINISHED |
| Object | short phrases |
—
|
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: short phrases | Statement: [Blue Purple Tilt, hasTextProperty, short phrases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTextProperty Context triple: [Blue Purple Tilt, hasTextProperty, short phrases]
-
A.
hasText
Indicates that an entity is associated with or contains a specific piece of textual content.
-
B.
hasTextElement
chosen
Indicates that an entity contains or is associated with a specific text-based component or segment.
-
C.
hasTextualCharacter
Indicates that something possesses or exhibits the qualities of written or printed text, such as letters, symbols, or characters.
-
D.
hasTextBy
Indicates that one entity (such as a document, work, or record) contains or is associated with text authored or written by another entity.
-
E.
hasNoText
Indicates that the referenced entity or element contains no textual content.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903094218819092e11b273d87de65 |
completed | April 10, 2026, 2:02 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3af0188190bfb22be5c97b3349 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.