Triple
T11153729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ehime Prefecture |
E263850
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Shikokuchūō
Shikokuchūō is an industrial city in Japan known as a major center for paper manufacturing on the island of Shikoku.
|
E1024727
|
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: Shikokuchūō | Statement: [Ehime Prefecture, hasCity, Shikokuchūō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shikokuchūō Context triple: [Ehime Prefecture, hasCity, Shikokuchūō]
-
A.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
-
B.
Shikaoi
Shikaoi is a rural town in Hokkaido, Japan, known for its natural scenery, agriculture, and access to outdoor activities such as hiking and hot springs.
-
C.
Nonoichi
Nonoichi is a city in Ishikawa Prefecture, Japan, known for its residential character and proximity to the regional hub of Kanazawa.
-
D.
Fukusaki
Fukusaki is a town in Hyōgo Prefecture, Japan, known for its rural setting and association with folklorist Kunio Yanagita.
-
E.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
- 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: Shikokuchūō Triple: [Ehime Prefecture, hasCity, Shikokuchūō]
Generated description
Shikokuchūō is an industrial city in Japan known as a major center for paper manufacturing on the island of Shikoku.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shikokuchūō Target entity description: Shikokuchūō is an industrial city in Japan known as a major center for paper manufacturing on the island of Shikoku.
-
A.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
-
B.
Shikaoi
Shikaoi is a rural town in Hokkaido, Japan, known for its natural scenery, agriculture, and access to outdoor activities such as hiking and hot springs.
-
C.
Nonoichi
Nonoichi is a city in Ishikawa Prefecture, Japan, known for its residential character and proximity to the regional hub of Kanazawa.
-
D.
Fukusaki
Fukusaki is a town in Hyōgo Prefecture, Japan, known for its rural setting and association with folklorist Kunio Yanagita.
-
E.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e872ffbc8190b8a3bbd912115342 |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eabf5ed88190b6de7b99b5ab590f |
completed | May 3, 2026, 6:27 a.m. |
| NEDg | Description generation | batch_69f6ee85e39081908bf3b244a5fed083 |
completed | May 3, 2026, 6:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6ef1310308190900b889a45b9da28 |
completed | May 3, 2026, 6:45 a.m. |
Created at: April 8, 2026, 9:28 p.m.