Triple
T7034894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuomintang headquarters, Taipei |
E163357
|
entity |
| Predicate | primaryScriptUsed |
P6524
|
FINISHED |
| Object | Traditional Chinese |
—
|
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: Traditional Chinese | Statement: [Kuomintang headquarters, Taipei, primaryScriptUsed, Traditional Chinese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryScriptUsed Context triple: [Kuomintang headquarters, Taipei, primaryScriptUsed, Traditional Chinese]
-
A.
primaryScript
chosen
Indicates the writing system or script that is chiefly used to represent the language or content of an entity.
-
B.
previousPrimaryScriptingLanguage
Indicates that an entity was formerly the main or primary scripting language used by another entity before being replaced or superseded.
-
C.
scriptUsedCurrently
Indicates that a particular writing system or script is the one presently in use for a given language, text, or context.
-
D.
scriptUsedForLanguage
Indicates that a particular writing script is employed to write or represent a given language.
-
E.
containsScript
Indicates that one entity includes or embeds the script of another entity within it.
- 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_69c6885d691c81908cf7d31083113886 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e458ad9c81908c3f492b317ce291 |
completed | March 27, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69c6e1b9a2488190aea351d96afa5a12 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:36 p.m.