Triple
T31440836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stickies |
E802060
|
entity |
| Predicate | textFormatting |
P135154
|
FINISHED |
| Object | fonts |
—
|
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: fonts | Statement: [Stickies, textFormatting, fonts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textFormatting Context triple: [Stickies, textFormatting, fonts]
-
A.
wordFormat
Indicates that one entity specifies the written or typographical form in which another entity (typically a word or text) is presented.
-
B.
textMode
Indicates that something operates, is displayed, or is processed in a mode where information is handled primarily as text rather than as graphics or other media.
-
C.
textualAppearance
chosen
Indicates how something is presented, formatted, or visually structured in written or printed text.
-
D.
textModes
Indicates a relationship where an entity supports or operates in specific textual modes or formats (such as plain text, rich text, or other text-based configurations).
-
E.
textType
Indicates the classification of a text according to its type, format, or genre.
- 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_69f348c5a6bc819092a557e95438976f |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a5f71b2c8190aade8a83f465be0c |
completed | May 3, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69f69fe66df08190958558d63ee623d9 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 30, 2026, 9:05 p.m.