Triple
T7892448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Urayasu, Chiba Prefecture |
E183267
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Maihama
Maihama is a coastal district of Urayasu in Chiba Prefecture, Japan, best known as the location of the Tokyo Disney Resort.
|
E704357
|
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: Maihama | Statement: [Urayasu, Chiba Prefecture, hasDistrict, Maihama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maihama Context triple: [Urayasu, Chiba Prefecture, hasDistrict, Maihama]
-
A.
Hatanodai
Hatanodai is a residential neighborhood in Tokyo, Japan, known for its local shopping streets and convenient rail connections.
-
B.
Nakanoshima
Nakanoshima is a small Japanese island associated with Etajima in Hiroshima Prefecture, known for its coastal scenery and role within the local island group.
-
C.
Hayama
Hayama is a coastal town in Kanagawa Prefecture, Japan, known for its beaches, scenic views of Sagami Bay, and as a site of an Imperial Villa.
-
D.
Higashimurayama
Higashimurayama is a suburban city in western Tokyo, Japan, known for its residential neighborhoods, parks, and role as part of the Tama area’s commuter belt.
-
E.
Itoshima
Itoshima is a coastal city in western Japan known for its scenic beaches, surf spots, and relaxed, nature-oriented lifestyle.
- 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: Maihama Triple: [Urayasu, Chiba Prefecture, hasDistrict, Maihama]
Generated description
Maihama is a coastal district of Urayasu in Chiba Prefecture, Japan, best known as the location of the Tokyo Disney Resort.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maihama Target entity description: Maihama is a coastal district of Urayasu in Chiba Prefecture, Japan, best known as the location of the Tokyo Disney Resort.
-
A.
Hatanodai
Hatanodai is a residential neighborhood in Tokyo, Japan, known for its local shopping streets and convenient rail connections.
-
B.
Nakanoshima
Nakanoshima is a small Japanese island associated with Etajima in Hiroshima Prefecture, known for its coastal scenery and role within the local island group.
-
C.
Hayama
Hayama is a coastal town in Kanagawa Prefecture, Japan, known for its beaches, scenic views of Sagami Bay, and as a site of an Imperial Villa.
-
D.
Higashimurayama
Higashimurayama is a suburban city in western Tokyo, Japan, known for its residential neighborhoods, parks, and role as part of the Tama area’s commuter belt.
-
E.
Itoshima
Itoshima is a coastal city in western Japan known for its scenic beaches, surf spots, and relaxed, nature-oriented lifestyle.
- 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_69ca828c474c8190a254d6499871eaff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39fef2e48190a6282c217c33c57a |
completed | March 31, 2026, 3:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbdfc1b05481908af081f54bb1914d |
completed | March 31, 2026, 2:52 p.m. |
| NEDg | Description generation | batch_69cbe4383d0c819085e7c95e7b0be16e |
completed | March 31, 2026, 3:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc34a83cec81908aba7afbaea53449 |
completed | March 31, 2026, 8:55 p.m. |
Created at: March 30, 2026, 5 p.m.