Triple
T13499383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sessue Hayakawa |
E320844
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Minamibōsō
Minamibōsō is a coastal city in Chiba Prefecture, Japan, known for its scenic Pacific shoreline, mild climate, and agricultural and fishing industries.
|
E1360013
|
NE FINISHED |
How this triple was built (4 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: Minamibōsō | Statement: [Sessue Hayakawa, placeOfBirth, Minamibōsō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Minamibōsō Context triple: [Sessue Hayakawa, placeOfBirth, Minamibōsō]
-
A.
Toyokawa
Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
-
B.
Kamaishi
Kamaishi is a coastal city in northeastern Japan known for its historic iron and steel industry and as a venue for the 2019 Rugby World Cup.
-
C.
Miyakonojō
Miyakonojō is a city in Miyazaki Prefecture on Japan’s Kyushu island, known for its agriculture and livestock production.
-
D.
Tsuruga
Tsuruga is a coastal city in Fukui Prefecture, Japan, known as a key port and transportation hub on the Sea of Japan side of Honshu.
-
E.
Okachimachi
Okachimachi is a bustling commercial and shopping district in Tokyo known for its discount stores, jewelry shops, and proximity to Ueno.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Minamibōsō Triple: [Sessue Hayakawa, placeOfBirth, Minamibōsō]
Generated description
Minamibōsō is a coastal city in Chiba Prefecture, Japan, known for its scenic Pacific shoreline, mild climate, and agricultural and fishing industries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Minamibōsō Target entity description: Minamibōsō is a coastal city in Chiba Prefecture, Japan, known for its scenic Pacific shoreline, mild climate, and agricultural and fishing industries.
-
A.
Toyokawa
Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
-
B.
Kamaishi
Kamaishi is a coastal city in northeastern Japan known for its historic iron and steel industry and as a venue for the 2019 Rugby World Cup.
-
C.
Miyakonojō
Miyakonojō is a city in Miyazaki Prefecture on Japan’s Kyushu island, known for its agriculture and livestock production.
-
D.
Tsuruga
Tsuruga is a coastal city in Fukui Prefecture, Japan, known as a key port and transportation hub on the Sea of Japan side of Honshu.
-
E.
Okachimachi
Okachimachi is a bustling commercial and shopping district in Tokyo known for its discount stores, jewelry shops, and proximity to Ueno.
- F. None of above. chosen
Provenance (5 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf4fab688190bdc746985b0c7338 |
completed | April 12, 2026, 2:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05e64fe7408190914a43f7c44872d7 |
completed | May 14, 2026, 3:12 p.m. |
| NEDg | Description generation | batch_6a05e96742c8819086680fb949f8f1bc |
completed | May 14, 2026, 3:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05ea69dea48190b97663a859645200 |
completed | May 14, 2026, 3:29 p.m. |
Created at: April 9, 2026, 9:43 p.m.