Triple
T15893239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koichi |
E385381
|
entity |
| Predicate | nameComponent |
P5298
|
FINISHED |
| Object | Kō |
E931374
|
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: Kō | Statement: [Koichi, nameComponent, Kō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kō Context triple: [Koichi, nameComponent, Kō]
-
A.
Ko
chosen
Ko is a Japanese given-name element commonly used in female names, often carrying meanings like “child” depending on the kanji used.
-
B.
Kōki
Kōki is a Japanese given name commonly used for males and borne by various notable figures in Japan.
-
C.
Kōjun
Kōjun was the posthumous name of Empress Kōjun, the wife of Emperor Shōwa (Hirohito) and mother of Emperor Emeritus Akihito of Japan.
-
D.
Kokonoe
Kokonoe is a small mountainous town in Japan known for its hot springs, scenic highlands, and suspension bridges.
-
E.
Koja
Koja is a coastal district in North Jakarta, Indonesia, known for its dense urban neighborhoods and proximity to the city’s port and industrial areas.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1563727cc819086b5c18b655dd7f6 |
completed | April 16, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb0497cb481908e8ea4ebb9c4039d |
completed | May 9, 2026, 10:08 p.m. |
Created at: April 10, 2026, 4:51 a.m.