Triple
T27402575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cia-Cia people |
E691892
|
entity |
| Predicate | writingSystemExperimentCityPartner |
P163263
|
FINISHED |
| Object | Seoul |
—
|
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: Seoul | Statement: [Cia-Cia people, writingSystemExperimentCityPartner, Seoul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writingSystemExperimentCityPartner Context triple: [Cia-Cia people, writingSystemExperimentCityPartner, Seoul]
-
A.
writingSystemExperimentPartner
chosen
Indicates that one entity participates as a partner or collaborator in an experiment involving a writing system with another entity.
-
B.
contentPartner
Indicates a relationship in which one entity collaborates with another to create, supply, or distribute content.
-
C.
cooperationPartner
Indicates that two entities are engaged in a collaborative relationship, working together toward shared goals or mutual benefit.
-
D.
writingSystemScope
Indicates the range or extent of content, languages, or contexts to which a particular writing system applies or is used.
-
E.
writingSystemCreator
Indicates that one entity is the creator or originator of the writing system used by another entity.
- 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_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c663be481908f233d25d28713a4 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 12:29 p.m.