Triple
T16151964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanzawa Mountains |
E391932
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Atsugi |
—
|
NE NERFINISHED |
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: Atsugi | Statement: [Tanzawa Mountains, near, Atsugi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Atsugi Context triple: [Tanzawa Mountains, near, Atsugi]
-
A.
Atsugi
chosen
Atsugi is a city in Kanagawa Prefecture, Japan, known as a regional commercial and industrial center with convenient access to the Tokyo metropolitan area.
-
B.
Asago
Asago is a city in northern Hyōgo Prefecture, Japan, known for its mountainous scenery, historic castle ruins, and hot spring resorts.
-
C.
Sakaide
Sakaide is a coastal city in Japan known for its industrial port facilities and its location near the Seto Ohashi Bridge in Kagawa Prefecture on Shikoku Island.
-
D.
Nakatane
Nakatane is a town on Tanegashima Island in Kagoshima Prefecture, Japan, known for its role in local administration and its proximity to the island’s space-related facilities and coastal scenery.
-
E.
Shimaore
Shimaore is a Bantu language closely related to Comorian, widely spoken by the local population of Mayotte in the Indian Ocean.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21d981950819087fdacc7879dca97 |
completed | April 17, 2026, 11:46 a.m. |
Created at: April 10, 2026, 5:01 a.m.