Triple
T573307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osaka Metro |
E13707
|
entity |
| Predicate | tertiaryLanguageOfSignage |
P16186
|
FINISHED |
| Object | 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: Chinese | Statement: [Osaka Metro, tertiaryLanguageOfSignage, Chinese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tertiaryLanguageOfSignage Context triple: [Osaka Metro, tertiaryLanguageOfSignage, Chinese]
-
A.
languageOfSignage
Indicates the language used on signs or written displays associated with an entity.
-
B.
hasSecondaryLanguage
Indicates that an entity possesses or uses a secondary language in addition to its primary language.
-
C.
languageOfOfficialAnnouncements
Indicates the language used for formal or official public announcements issued by an authority.
-
D.
standardLanguageOf
Indicates that one entity serves as the officially recognized or commonly used standard language for another entity (such as a country, region, or organization).
-
E.
hasSignificantLanguage
Indicates that an entity possesses a language that plays an important or primary role in its communication, identity, or functioning.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b4ae0988190bdd0ad428b784d85 |
completed | March 1, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69a494c4969c819080375d08f9eec50c |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a498dd579081908e02368a4c5efc8c |
completed | March 1, 2026, 7:51 p.m. |
Created at: March 1, 2026, 7:33 p.m.