Triple
T10626122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corinthia regional unit |
E250327
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Kiato |
E288757
|
NE 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: Kiato | Statement: [Corinthia regional unit, contains, Kiato]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiato Context triple: [Corinthia regional unit, contains, Kiato]
-
A.
Kiato
chosen
Kiato is a coastal town in the northern Peloponnese of Greece, serving as a local commercial and transportation hub within the regional unit of Corinthia.
-
B.
Kiso
Kiso is a town in Nagano Prefecture, Japan, known for its scenic Kiso Valley, traditional post towns on the old Nakasendō route, and proximity to Mount Ontake.
-
C.
Kitanemuk
Kitanemuk is an extinct Uto-Aztecan language once spoken by the Kitanemuk people in what is now Southern California.
-
D.
Taketa
Taketa is a small historic city in Japan known for its scenic rural landscapes, hot springs, and castle ruins.
-
E.
Kiamu
Kiamu is a dialect of the Swahili language traditionally spoken in the Lamu (Amu) region of Kenya.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df80a30c81909f36fe221cf68822 |
completed | April 8, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96ba260b48190a5bde201ee3df69a |
completed | April 10, 2026, 9:29 p.m. |
Created at: April 8, 2026, 8:54 p.m.