Triple
T12366662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | If My Heart Had Wings |
E294889
|
entity |
| Predicate | setting |
P1957
|
FINISHED |
| Object |
Kazegaura
Kazegaura is a tranquil, wind-swept lakeside town in the visual novel "If My Heart Had Wings," known for its scenic vistas and serene atmosphere.
|
E1239012
|
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: Kazegaura | Statement: [If My Heart Had Wings, setting, Kazegaura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kazegaura Context triple: [If My Heart Had Wings, setting, Kazegaura]
-
A.
Higashikurume
Higashikurume is a suburban city in western Tokyo, Japan, known for its residential neighborhoods and role as a commuter area for central Tokyo.
-
B.
Shikaoi
Shikaoi is a rural town in Hokkaido, Japan, known for its natural scenery, agriculture, and access to outdoor activities such as hiking and hot springs.
-
C.
Akiruno
Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
-
D.
Yokoze
Yokoze is a small town in Saitama Prefecture, Japan, known for its rural scenery and proximity to the Chichibu mountain area.
-
E.
Fukusaki
Fukusaki is a town in Hyōgo Prefecture, Japan, known for its rural setting and association with folklorist Kunio Yanagita.
- 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: Kazegaura Triple: [If My Heart Had Wings, setting, Kazegaura]
Generated description
Kazegaura is a tranquil, wind-swept lakeside town in the visual novel "If My Heart Had Wings," known for its scenic vistas and serene atmosphere.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kazegaura Target entity description: Kazegaura is a tranquil, wind-swept lakeside town in the visual novel "If My Heart Had Wings," known for its scenic vistas and serene atmosphere.
-
A.
Higashikurume
Higashikurume is a suburban city in western Tokyo, Japan, known for its residential neighborhoods and role as a commuter area for central Tokyo.
-
B.
Shikaoi
Shikaoi is a rural town in Hokkaido, Japan, known for its natural scenery, agriculture, and access to outdoor activities such as hiking and hot springs.
-
C.
Akiruno
Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
-
D.
Yokoze
Yokoze is a small town in Saitama Prefecture, Japan, known for its rural scenery and proximity to the Chichibu mountain area.
-
E.
Fukusaki
Fukusaki is a town in Hyōgo Prefecture, Japan, known for its rural setting and association with folklorist Kunio Yanagita.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93fa502988190ba170dee90d9f394 |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c28d1e1c81909e869f01659ec233 |
completed | May 10, 2026, 5:38 p.m. |
| NEDg | Description generation | batch_6a00c457a1608190bd57155e91e55e9c |
completed | May 10, 2026, 5:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00c5230fd481908cbc37e332b72380 |
completed | May 10, 2026, 5:49 p.m. |
Created at: April 8, 2026, 9:54 p.m.