Triple
T27402574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cia-Cia people |
E691892
|
entity |
| Predicate | writingSystemExperimentCountryPartner |
P163263
|
FINISHED |
| Object | South Korea |
—
|
NE NERFINISHED |
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: South Korea | Statement: [Cia-Cia people, writingSystemExperimentCountryPartner, South Korea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writingSystemExperimentCountryPartner Context triple: [Cia-Cia people, writingSystemExperimentCountryPartner, South Korea]
-
A.
writingSystemExperimentPartner
chosen
Indicates that one entity participates as a partner or collaborator in an experiment involving a writing system with another entity.
-
B.
collaborationCountry
Indicates that there is a collaborative relationship or joint activity involving entities associated with the specified country.
-
C.
countryPartner
Indicates a formal partnership relationship between two countries, such as cooperation, alliance, or strategic collaboration.
-
D.
contentPartner
Indicates a relationship in which one entity collaborates with another to create, supply, or distribute content.
-
E.
writtenInCountry
Indicates that a written work was created, authored, or composed within the geographical boundaries of a specific country.
- 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_69ef5204f7048190bf226a129858fc5b |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f6383625cc8190aa223d8ef655743c |
completed | May 2, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69f63709e4848190b5cf322e06b23fb6 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 12:29 p.m.