Triple
T13391048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamakura |
E319571
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Inamuragasaki
Inamuragasaki is a scenic coastal cape and beach area in Kamakura, Japan, known for its ocean views, sunsets, and historical significance.
|
E1191404
|
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: Inamuragasaki | Statement: [Kamakura, hasLandmark, Inamuragasaki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inamuragasaki Context triple: [Kamakura, hasLandmark, Inamuragasaki]
-
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.
Ayabe
Ayabe is a small city in the northern part of Japan’s Kyoto Prefecture, known for its rural landscapes, traditional industries, and spiritual retreat centers.
-
C.
Kamaishi
Kamaishi is a coastal city in northeastern Japan known for its historic iron and steel industry and as a venue for the 2019 Rugby World Cup.
-
D.
Saijo
Saijo is a city in Ehime Prefecture on Japan’s Shikoku island, known for its industrial facilities and maritime-related industries.
-
E.
Noshiro
Noshiro is a coastal city in northern Japan known for its port on the Sea of Japan and its forestry and basketball traditions.
- 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: Inamuragasaki Triple: [Kamakura, hasLandmark, Inamuragasaki]
Generated description
Inamuragasaki is a scenic coastal cape and beach area in Kamakura, Japan, known for its ocean views, sunsets, and historical significance.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Inamuragasaki Target entity description: Inamuragasaki is a scenic coastal cape and beach area in Kamakura, Japan, known for its ocean views, sunsets, and historical significance.
-
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.
Ayabe
Ayabe is a small city in the northern part of Japan’s Kyoto Prefecture, known for its rural landscapes, traditional industries, and spiritual retreat centers.
-
C.
Kamaishi
Kamaishi is a coastal city in northeastern Japan known for its historic iron and steel industry and as a venue for the 2019 Rugby World Cup.
-
D.
Saijo
Saijo is a city in Ehime Prefecture on Japan’s Shikoku island, known for its industrial facilities and maritime-related industries.
-
E.
Noshiro
Noshiro is a coastal city in northern Japan known for its port on the Sea of Japan and its forestry and basketball traditions.
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dba0d543348190a9c1be509b015c0f |
completed | April 12, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbb445a48190ba3dafb1f076ac83 |
completed | May 10, 2026, 1:13 a.m. |
| NEDg | Description generation | batch_69ffdd3c77908190b55c926445724348 |
completed | May 10, 2026, 1:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffddfdd3a48190a16dab4d458dc475 |
completed | May 10, 2026, 1:23 a.m. |
Created at: April 9, 2026, 9:34 p.m.