Triple
T5233215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese Buddhism |
E118156
|
entity |
| Predicate | hasCenter |
P35
|
FINISHED |
| Object | Mount Emei |
E211984
|
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: Mount Emei | Statement: [Chinese Buddhism, hasCenter, Mount Emei]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Emei Context triple: [Chinese Buddhism, hasCenter, Mount Emei]
-
A.
Mount Emei
chosen
Mount Emei is one of China’s Four Sacred Buddhist Mountains, renowned for its ancient temples, rich biodiversity, and dramatic, cloud-wreathed peaks.
-
B.
Mount Tai
Mount Tai is one of China’s most famous and historically significant sacred mountains, revered in Chinese religion and culture for millennia.
-
C.
Chihsing Mountain
Chihsing Mountain is a volcanic peak in Yangmingshan National Park near Taipei, Taiwan, known as the highest mountain in the Taipei area and a popular hiking destination.
-
D.
Tianzhu Peak
Tianzhu Peak is the tallest summit of China’s Wudang Mountains, a range famed for its Taoist temples and martial arts heritage.
-
E.
Moganshan
Moganshan is a scenic, bamboo-covered mountain resort area in eastern China known for its cool climate, hiking trails, and historic villas.
- 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_69bd4466fb8c819083b806a79414d7e4 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b0389048190b55b7c44fe657044 |
completed | March 20, 2026, 4:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bef8154940819098ed76e14804f4b3 |
completed | March 21, 2026, 7:57 p.m. |
Created at: March 20, 2026, 1:49 p.m.