Triple
T21090367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mie Hama |
E519621
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Mie |
—
|
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: Mie | Statement: [Mie Hama, givenName, Mie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mie Context triple: [Mie Hama, givenName, Mie]
-
A.
Mie
chosen
Mie is a prefecture in central Japan known for its coastal landscapes, historic Ise Grand Shrine, and traditional pearl cultivation.
-
B.
Mien
Mien are an ethnic group of the Yao minority in East and Southeast Asia, known for their distinct language, traditional dress, and mountain village communities.
-
C.
Miyaki
Miyaki is a town in Saga Prefecture, Japan, known for its cultural and municipal exchange partnerships with European communities such as Rheinbach in Germany.
-
D.
Miyuki
Miyuki is a Japanese given name commonly used for women and associated with meanings such as "beautiful happiness" or "deep snow," depending on the kanji used.
-
E.
Mibuchi
Mibuchi is a Japanese surname borne by individuals such as Tadahiko Mibuchi.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b507dd9081908fb8bfcbef4c8b46 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7094ea7f881909db83bf6961b41ec |
completed | April 21, 2026, 5:21 a.m. |
Created at: April 16, 2026, 2:50 p.m.