Triple
T7026897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gwangju Metro |
E162970
|
entity |
| Predicate | hasScriptOnSignage |
P47313
|
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: [Gwangju Metro, hasScriptOnSignage, Hangul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScriptOnSignage Context triple: [Gwangju Metro, hasScriptOnSignage, Hangul]
-
A.
scriptUsedInSignage
chosen
Indicates that a particular writing system or script is employed in the text or graphics of a sign or signage.
-
B.
hasSignage
Indicates that appropriate signs or visual markers are present to convey information, directions, warnings, or identification related to the associated entity.
-
C.
hasSignageIn
Indicates that appropriate signs or signage for an entity are present or installed within a specified location or area.
-
D.
hasSignageType
Indicates the specific category or kind of signage associated with an object, location, or entity.
-
E.
hasSignageName
Indicates that an entity has a specific name or label as it appears on its physical signage.
- 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_69c6885b26248190a857541e3d10e299 |
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, 2:35 p.m.