Triple
T12464562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evangelical Lutheran Church of Taiwan |
E297887
|
entity |
| Predicate | hasLanguageOfMinistry |
P101845
|
FINISHED |
| Object | Mandarin 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: Mandarin Chinese | Statement: [Evangelical Lutheran Church of Taiwan, hasLanguageOfMinistry, Mandarin Chinese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfMinistry Context triple: [Evangelical Lutheran Church of Taiwan, hasLanguageOfMinistry, Mandarin Chinese]
-
A.
hasOfficerLanguage
Indicates that an officer is able or authorized to communicate in a specified language.
-
B.
hasLanguageOfOfficialName
Indicates that an entity’s official name is expressed in a specified language.
-
C.
hasNotableLanguageWithOfficialStatusIn
Indicates that a language holds an officially recognized and notable status within a specified jurisdiction or region.
-
D.
methodOfMinistry
Indicates the specific way or approach through which ministry or religious service is carried out.
-
E.
hasMinorityLanguageServices
chosen
Indicates that an entity provides services specifically tailored for speakers of minority or less widely used languages.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e626dbc8190ac7dcdb542ba9b0c |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d3f701c81909dd0e00251ac8553 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.