Triple
T16124324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jōzankei Onsen |
E391226
|
entity |
| Predicate | hasAttraction |
P105
|
FINISHED |
| Object | Hoheikyo Dam |
E768475
|
NE FINISHED |
How this triple was built (2 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: Hoheikyo Dam | Statement: [Jōzankei Onsen, hasAttraction, Hoheikyo Dam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hoheikyo Dam Context triple: [Jōzankei Onsen, hasAttraction, Hoheikyo Dam]
-
A.
Hoheikyo Dam
chosen
Hoheikyo Dam is a concrete arch dam in the mountainous outskirts of Sapporo, Japan, known for its scenic reservoir, autumn foliage, and nearby hot spring resorts.
-
B.
Kindaruma Dam
Kindaruma Dam is one of Kenya’s major hydroelectric power stations on the Tana River, contributing significantly to the country’s electricity generation.
-
C.
Ukai Dam
Ukai Dam is a major multi-purpose reservoir and hydroelectric dam in Gujarat, India, built on the Tapi River for irrigation, power generation, and flood control.
-
D.
Koka Dam
Koka Dam is a major hydroelectric and irrigation dam in Ethiopia that creates the Koka Reservoir on the Awash River.
-
E.
Nagayasuguchi Dam
Nagayasuguchi Dam is a hydroelectric dam located on Japan’s Yoshino River, used primarily for power generation and flood control.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2020342988190add65c784b8ee179 |
completed | April 17, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff79ecea0819083aa5cb676d49f64 |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 5 a.m.