Triple
T20203139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trachis |
E493275
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Mount Oeta |
—
|
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: Mount Oeta | Statement: [Trachis, locatedNear, Mount Oeta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Oeta Context triple: [Trachis, locatedNear, Mount Oeta]
-
A.
Mount Oeta
chosen
Mount Oeta is a mountain in central Greece famed in Greek mythology as the site of Heracles’ death and apotheosis.
-
B.
Mount Tairyu
Mount Tairyu is a mountain in Tokushima Prefecture, Japan, best known as the site of Tairyuji, the 21st temple on the Shikoku Pilgrimage.
-
C.
Mount Suiro
Mount Suiro is the tallest mountain on Biliran Island in the Philippines, forming a prominent part of the island’s volcanic landscape.
-
D.
Mount Erice
Mount Erice is a prominent mountain in western Sicily, Italy, known for its medieval hilltop town of Erice and panoramic views over the surrounding coast and islands.
-
E.
Mount Goryu
Mount Goryu is a prominent peak in Japan’s Northern Alps, known for its ski resorts and alpine hiking within the Hakuba Valley area.
- 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_69da6269614c8190bb40475d9d477358 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66d8ec73c8190b630599c5ceb22ac |
completed | April 20, 2026, 6:16 p.m. |
Created at: April 11, 2026, 11:38 p.m.