Triple
T15373024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lutsi dialect |
E367595
|
entity |
| Predicate | hasLexicalSimilarityWith |
P11829
|
FINISHED |
| Object | Seto |
E74279
|
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: Seto | Statement: [Lutsi dialect, hasLexicalSimilarityWith, Seto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seto Context triple: [Lutsi dialect, hasLexicalSimilarityWith, Seto]
-
A.
Seto
chosen
Seto is a South Estonian dialect and cultural variety spoken by the Seto people, known for its distinct linguistic features and rich folk traditions.
-
B.
Seto
Seto is a city in Kagawa Prefecture, Japan, known for its traditional ceramics and role as a regional cultural and industrial center.
-
C.
Seto Naikai
Seto Naikai is a scenic body of water in western Japan, dotted with islands and known for its mild climate, historic trade routes, and picturesque coastal landscapes.
-
D.
Ninoshima
Ninoshima is a small island in Japan known for its location near Hiroshima and its historical role during and after the atomic bombing of Hiroshima in World War II.
-
E.
Nambui
Nambui was a Mongol empress consort of the Yuan dynasty and a prominent wife of Kublai Khan, influential in the imperial court after the death of his first empress.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e5c1d548190930bfaf0861595ae |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b528f408190b66d3d6e10e90a43 |
completed | May 9, 2026, 10:24 a.m. |
Created at: April 10, 2026, 3:18 a.m.