Triple
T10014932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aichi Prefecture |
E199464
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Takahama
Takahama is a small coastal city in central Japan known for its industrial activity and location within Aichi Prefecture.
|
E988561
|
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: Takahama | Statement: [Aichi Prefecture, containsCity, Takahama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Takahama Context triple: [Aichi Prefecture, containsCity, Takahama]
-
A.
Yanagawa
Yanagawa is a historic canal city in southwestern Japan known for its picturesque waterways, traditional boat tours, and former castle-town atmosphere.
-
B.
Higashikawa
Higashikawa is a town in Hokkaido, Japan, known as a gateway to the Daisetsuzan mountain range and for its scenic natural landscapes.
-
C.
Yurihonjō
Yurihonjō is a coastal city in Akita Prefecture, Japan, known for its rice farming, sake production, and scenic Sea of Japan shoreline.
-
D.
Toyokawa
Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
-
E.
Fujieda
Fujieda is a city in Shizuoka Prefecture, Japan, known as a regional commercial center with a mix of residential areas, agriculture, and light industry.
- 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: Takahama Triple: [Aichi Prefecture, containsCity, Takahama]
Generated description
Takahama is a small coastal city in central Japan known for its industrial activity and location within Aichi Prefecture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Takahama Target entity description: Takahama is a small coastal city in central Japan known for its industrial activity and location within Aichi Prefecture.
-
A.
Yanagawa
Yanagawa is a historic canal city in southwestern Japan known for its picturesque waterways, traditional boat tours, and former castle-town atmosphere.
-
B.
Higashikawa
Higashikawa is a town in Hokkaido, Japan, known as a gateway to the Daisetsuzan mountain range and for its scenic natural landscapes.
-
C.
Yurihonjō
Yurihonjō is a coastal city in Akita Prefecture, Japan, known for its rice farming, sake production, and scenic Sea of Japan shoreline.
-
D.
Toyokawa
Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
-
E.
Fujieda
Fujieda is a city in Shizuoka Prefecture, Japan, known as a regional commercial center with a mix of residential areas, agriculture, and light industry.
- 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_69f6554d0b0081909cc031ff06b796c0 |
completed | May 2, 2026, 7:49 p.m. |
| NEDg | Description generation | batch_69f6566dccc0819085e059c7b0288f6c |
completed | May 2, 2026, 7:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f657aec8fc8190b3b08ccb95595958 |
completed | May 2, 2026, 7:59 p.m. |
Created at: March 30, 2026, 8:52 p.m.