Triple
T15282117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | flag of Valencia |
E365293
|
entity |
| Predicate | scriptDirectionOnOrnaments |
P117943
|
FINISHED |
| Object | left-to-right |
—
|
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: left-to-right | Statement: [flag of Valencia, scriptDirectionOnOrnaments, left-to-right]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptDirectionOnOrnaments Context triple: [flag of Valencia, scriptDirectionOnOrnaments, left-to-right]
-
A.
ornamentationStyle
Indicates the decorative design or stylistic approach applied as ornamentation to an entity.
-
B.
hasOrnamentation
Indicates that an entity possesses decorative features or embellishments applied to its surface or structure.
-
C.
musicalDirection
Indicates that one entity provides guidance, leadership, or control over the musical aspects or performance of another entity.
-
D.
scriptDirection
Indicates the direction in which a writing system or script is read or written (e.g., left-to-right, right-to-left, top-to-bottom).
-
E.
notableOrnamental
Indicates that something is recognized as a particularly significant or distinguished example of ornamental decoration or design.
- F. None of above. chosen
Provenance (4 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00e51f82081909f63d14b589d5587 |
completed | April 15, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69deca90739081909bd1b797cdb8af2b |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2e413481909d9180a8d78d2c17 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:15 a.m.