Triple
T10014947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aichi Prefecture |
E199464
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Taketoyo
Taketoyo is a coastal town in central Japan known for its industrial facilities and location within Aichi Prefecture.
|
E945089
|
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: Taketoyo | Statement: [Aichi Prefecture, containsCity, Taketoyo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taketoyo Context triple: [Aichi Prefecture, containsCity, Taketoyo]
-
A.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
-
B.
Kantokuen
Kantokuen was an Imperial Japanese Army war plan developed in 1941 for a large-scale invasion of the Soviet Far East from Manchuria.
-
C.
Hakutaka
Hakutaka is a high-speed train service operating on Japan’s Hokuriku Shinkansen line, connecting Tokyo with cities along the Sea of Japan coast.
-
D.
Takaishi
Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
-
E.
Tokoname
Tokoname is a coastal city in Aichi Prefecture, Japan, historically renowned as one of the country’s Six Ancient Kilns for its distinctive ceramic and pottery production.
- 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: Taketoyo Triple: [Aichi Prefecture, containsCity, Taketoyo]
Generated description
Taketoyo is a coastal town in central Japan known for its industrial facilities and location within Aichi Prefecture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Taketoyo Target entity description: Taketoyo is a coastal town in central Japan known for its industrial facilities and location within Aichi Prefecture.
-
A.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
-
B.
Kantokuen
Kantokuen was an Imperial Japanese Army war plan developed in 1941 for a large-scale invasion of the Soviet Far East from Manchuria.
-
C.
Hakutaka
Hakutaka is a high-speed train service operating on Japan’s Hokuriku Shinkansen line, connecting Tokyo with cities along the Sea of Japan coast.
-
D.
Takaishi
Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
-
E.
Tokoname
Tokoname is a coastal city in Aichi Prefecture, Japan, historically renowned as one of the country’s Six Ancient Kilns for its distinctive ceramic and pottery production.
- 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_69ca8315a1a08190ab310f25620f362b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd49b19c8190b429e3533d072648 |
completed | April 2, 2026, 1:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f08ec96fe88190b791e6f50f39173f |
completed | April 28, 2026, 10:41 a.m. |
| NEDg | Description generation | batch_69f0bd36673881908530b68e496c3d2e |
completed | April 28, 2026, 1:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f0eec1f5d081908624fe2a93995fe5 |
completed | April 28, 2026, 5:30 p.m. |
Created at: March 30, 2026, 8:52 p.m.