Triple
T8391867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midori Ito |
E197961
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Ito |
E452962
|
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: Ito | Statement: [Midori Ito, familyName, Ito]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ito Context triple: [Midori Ito, familyName, Ito]
-
A.
Ogawa
Ogawa is a town in Saitama Prefecture, Japan, known for its traditional Japanese paper (washi) production and its role as a local transport hub.
-
B.
Itō
chosen
Itō is a common Japanese surname borne by numerous notable figures in fields such as politics, the military, arts, and sciences.
-
C.
Izumi
Izumi is a city located in Osaka Prefecture, Japan, known as a residential and commercial hub in the Kansai region.
-
D.
Tagawa
Tagawa is a small inland city in Japan known historically as a coal-mining center within Fukuoka Prefecture on Kyushu Island.
-
E.
Minamishinagawa
Minamishinagawa is a neighborhood in Tokyo’s Shinagawa ward known for its mix of residential streets, local shops, and proximity to major transport hubs.
- 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_69ca82f749388190bffbea6dfb509016 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb810e16b081908e2c25bfb9d590ed |
completed | March 31, 2026, 8:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde84d6f3c8190ba12905ba5900087 |
completed | April 2, 2026, 3:53 a.m. |
Created at: March 30, 2026, 6:03 p.m.