Triple
T10813996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saitama Prefectural flag |
E255176
|
entity |
| Predicate | scriptRepresented |
P20268
|
FINISHED |
| Object | katakana |
—
|
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: katakana | Statement: [Saitama Prefectural flag, scriptRepresented, katakana]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptRepresented Context triple: [Saitama Prefectural flag, scriptRepresented, katakana]
-
A.
scriptRepresentation
chosen
Indicates the specific written or encoded form in which something (such as language, data, or content) is expressed or represented.
-
B.
scriptOfReferent
Indicates that a script (e.g., writing system or code) is associated with, or used to represent, a particular referent.
-
C.
representationIn
Indicates that one entity serves as a depiction, model, or stand-in for another entity within a given context or medium.
-
D.
representation
Indicates that one entity stands in for, symbolizes, or depicts another entity in some context.
-
E.
scriptVariantOf
Indicates that one script is a variant or alternative form of another script, typically differing in style, region, or historical development while remaining closely related.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733eba9b48190b4dbe7fe5d8be0a4 |
completed | April 9, 2026, 5:06 a.m. |
| PD | Predicate disambiguation | batch_69d70d1bf3648190b36fa96ea018e0dc |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:18 p.m.