Triple
T10529975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yamaguchi Prefecture |
E248411
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Kudamatsu
Kudamatsu is a coastal city in western Japan known for its industrial facilities and location along the Seto Inland Sea in Yamaguchi Prefecture.
|
E1021311
|
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: Kudamatsu | Statement: [Yamaguchi Prefecture, hasCity, Kudamatsu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kudamatsu Context triple: [Yamaguchi Prefecture, hasCity, Kudamatsu]
-
A.
Kanramachi
Kanramachi is a Japanese town known for its cultural and municipal partnership with the Italian town of Certaldo.
-
B.
Kumagaya
Kumagaya is a city in northern Saitama Prefecture, Japan, known for its hot summer temperatures and role as a regional commercial and transportation hub.
-
C.
Shibukawa
Shibukawa is a city in Gunma Prefecture, Japan, known as a regional transport hub and gateway to nearby hot spring resorts such as Ikaho Onsen.
-
D.
Fukusaki
Fukusaki is a town in Hyōgo Prefecture, Japan, known for its rural setting and association with folklorist Kunio Yanagita.
-
E.
Izumisano
Izumisano is a coastal city in Osaka Prefecture, Japan, known as the mainland gateway to Kansai International Airport and a hub for regional commerce and travel.
- 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: Kudamatsu Triple: [Yamaguchi Prefecture, hasCity, Kudamatsu]
Generated description
Kudamatsu is a coastal city in western Japan known for its industrial facilities and location along the Seto Inland Sea in Yamaguchi Prefecture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kudamatsu Target entity description: Kudamatsu is a coastal city in western Japan known for its industrial facilities and location along the Seto Inland Sea in Yamaguchi Prefecture.
-
A.
Kanramachi
Kanramachi is a Japanese town known for its cultural and municipal partnership with the Italian town of Certaldo.
-
B.
Kumagaya
Kumagaya is a city in northern Saitama Prefecture, Japan, known for its hot summer temperatures and role as a regional commercial and transportation hub.
-
C.
Shibukawa
Shibukawa is a city in Gunma Prefecture, Japan, known as a regional transport hub and gateway to nearby hot spring resorts such as Ikaho Onsen.
-
D.
Fukusaki
Fukusaki is a town in Hyōgo Prefecture, Japan, known for its rural setting and association with folklorist Kunio Yanagita.
-
E.
Izumisano
Izumisano is a coastal city in Osaka Prefecture, Japan, known as the mainland gateway to Kansai International Airport and a hub for regional commerce and travel.
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509f7d8ac8190b90c1a7f77b23545 |
completed | April 7, 2026, 1:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e2527570819092314ee0a678e53c |
completed | May 3, 2026, 5:51 a.m. |
| NEDg | Description generation | batch_69f6e32bf5508190b4dc58971f8f64d0 |
completed | May 3, 2026, 5:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6e407dd988190b928b8931985a815 |
completed | May 3, 2026, 5:58 a.m. |
Created at: April 6, 2026, 12:30 p.m.