Triple
T3310530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Japan |
E69559
|
entity |
| Predicate | hasHistoricalCity |
P3786
|
FINISHED |
| Object | Nara |
E18488
|
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: Nara | Statement: [Western Japan, hasHistoricalCity, Nara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nara Context triple: [Western Japan, hasHistoricalCity, Nara]
-
A.
Nara
chosen
Nara is an ancient Japanese city renowned for its early role as a national capital, its historic temples, and its culturally significant deer-filled parks.
-
B.
Nara
Nara is a Nilo-Saharan language spoken by the Nara people, an ethnic minority primarily living in western Eritrea.
-
C.
Meijō
Meijō is the Japanese name for Nagoya Castle, a historic and iconic samurai-era fortress in Nagoya, Japan.
-
D.
Kyoto
Kyoto is a historic Japanese city renowned for its well-preserved temples, traditional wooden houses, and role as the former imperial capital.
-
E.
Sendai
Sendai is the largest city in Japan’s Tōhoku region, known for its lush greenery, historic sites, and status as a major economic and cultural center in northeastern Honshu.
- 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_69ad859f218081909458d2cebbf57565 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0eb6dd08190bab1ce80f417966a |
completed | March 8, 2026, 5:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b37e4d4d948190b74116d1d21dc519 |
completed | March 13, 2026, 3:02 a.m. |
Created at: March 8, 2026, 3:11 p.m.