Triple
T1173479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emblem of South Korea |
E24964
|
entity |
| Predicate | scriptOnRibbon |
P26218
|
FINISHED |
| Object | Hangul |
—
|
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: Hangul | Statement: [Emblem of South Korea, scriptOnRibbon, Hangul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptOnRibbon Context triple: [Emblem of South Korea, scriptOnRibbon, Hangul]
-
A.
scriptOnFlag
Indicates that a script is attached to and/or executed when a specific flag or condition is set.
-
B.
scriptType
Indicates the classification or category of a script, specifying what kind of script it is (e.g., its format, purpose, or scripting language type).
-
C.
scriptCategory
Indicates the classification or type of script to which an entity (such as a written work, code, or performance text) belongs.
-
D.
scriptRepresentation
Indicates the specific written or encoded form in which something (such as language, data, or content) is expressed or represented.
-
E.
scriptCode
Indicates that an entity is associated with a particular writing system or script, identified by a standardized script code.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd53e4b48190abb2167f8074a6bc |
completed | March 1, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5844348190b01ac6506906ba3b |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bd52177081908c5cec8e731b836e |
completed | March 1, 2026, 10:27 p.m. |
Created at: March 1, 2026, 7:45 p.m.