Triple
T8781012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shibuya |
E208724
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Sasazuka |
E30948
|
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: Sasazuka | Statement: [Shibuya, contains, Sasazuka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sasazuka Context triple: [Shibuya, contains, Sasazuka]
-
A.
Sasazuka
chosen
Sasazuka is a residential and commercial neighborhood in Tokyo known for its convenient access to central Shibuya and its mix of traditional shopping streets and modern urban living.
-
B.
Akizuki
Akizuki was a Japanese Akizuki-class destroyer of the Imperial Japanese Navy that served in World War II before being sunk in the Battle off Cape Engaño in 1944.
-
C.
Suzuya
Suzuya is a Japanese Mogami-class heavy cruiser of the Imperial Japanese Navy that served during World War II.
-
D.
Katsuragi
Katsuragi is a city in Japan known for its location in Nara Prefecture and its historical and cultural ties to the ancient Yamato region.
-
E.
Katsuragi
Katsuragi was a late-war Imperial Japanese Navy aircraft carrier that served in the Pacific Theater during World War II.
- 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_69ca835fbee88190bf625939bac48d7f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f55b7b08190ab3e18cd634a144b |
completed | March 31, 2026, 11:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf51df4a608190883a093dbd169976 |
completed | April 3, 2026, 5:36 a.m. |
Created at: March 30, 2026, 6:42 p.m.