Triple
T13875441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kōtō |
E333569
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Tatsumi |
E795410
|
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: Tatsumi | Statement: [Kōtō, contains, Tatsumi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tatsumi Context triple: [Kōtō, contains, Tatsumi]
-
A.
Tatsumi
chosen
Tatsumi is a masculine Japanese given name commonly used for boys and borne by various notable figures in Japan.
-
B.
Takanami
Takanami was a Japanese destroyer of the Imperial Japanese Navy during World War II, notable for being sunk in the Battle of Tassafaronga in 1942.
-
C.
Tateishi
Tateishi is a neighborhood in Tokyo known for its traditional shitamachi atmosphere, narrow shopping streets, and old-style bars and eateries.
-
D.
Kentarō
Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
-
E.
Takaichi
Takaichi is a Japanese surname most prominently associated with conservative politician Sanae Takaichi.
- 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0be556708190bbcf0b3583f677e3 |
completed | April 14, 2026, 9:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec86c6c6c8190957e398e3dcdd840 |
completed | May 9, 2026, 5:38 a.m. |
Created at: April 9, 2026, 10:15 p.m.