Triple
T15487921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Izena Island |
E377099
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Nakama |
E515175
|
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: Nakama | Statement: [Izena Island, hasSettlement, Nakama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nakama Context triple: [Izena Island, hasSettlement, Nakama]
-
A.
Nakama
chosen
Nakama is a city located in Japan’s Fukuoka Prefecture on the island of Kyushu.
-
B.
Shikai
Shikai is the given name of Yuan Shikai, the Chinese military and political leader who became the first president of the Republic of China.
-
C.
Tameyoshi
Tameyoshi was a Heian-period Japanese samurai leader of the Minamoto clan who played a key role in early clan conflicts that preceded the Genpei War.
-
D.
Tatsugō
Tatsugō is a small town located on Amami Ōshima in Japan’s Kagoshima Prefecture, known for its subtropical climate and island scenery.
-
E.
Usaka
Usaka is a town in the Ikwuano local government area of Abia State in southeastern Nigeria.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03faaca588190b0397bc2e27a522a |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff365d45488190b48458092b6ffead |
completed | May 9, 2026, 1:27 p.m. |
Created at: April 10, 2026, 3:48 a.m.