Triple
T262068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo |
E5560
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object | Shibuya Crossing |
E25403
|
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: Shibuya Crossing | Statement: [Tokyo, hasLandmark, Shibuya Crossing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shibuya Crossing Context triple: [Tokyo, hasLandmark, Shibuya Crossing]
-
A.
Shibuya Crossing
chosen
Shibuya Crossing is a famous and extremely busy pedestrian scramble intersection in Tokyo, often seen as a symbol of the city's vibrant urban life.
-
B.
Shibuya Scramble Square
Shibuya Scramble Square is a high-rise commercial complex in Tokyo featuring offices, shops, restaurants, and an observation deck overlooking the famous Shibuya Crossing.
-
C.
Hachiko Square
Hachiko Square is a famous public plaza in Shibuya known as a popular meeting spot near Shibuya Station, named after the loyal dog Hachiko.
-
D.
Shibuya Station
Shibuya Station is one of Tokyo’s busiest and most important railway hubs, serving multiple train and subway lines and anchoring the famous Shibuya shopping and entertainment district.
-
E.
Tokyo Station
Tokyo Station is a major railway hub in central Tokyo, serving as a key terminal for Shinkansen bullet trains and numerous local and regional lines.
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25d7428dc8190ae12b12a21fcc6cb |
completed | Feb. 28, 2026, 3:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a38b8ca1f08190a13733c03b9161f9 |
completed | March 1, 2026, 12:42 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.