Triple
T1102172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shibuya Crossing |
E25403
|
entity |
| Predicate | pedestriansCanCross |
P23122
|
FINISHED |
| Object | inAllDirectionsSimultaneously |
—
|
LITERAL 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: inAllDirectionsSimultaneously | Statement: [Shibuya Crossing, pedestriansCanCross, inAllDirectionsSimultaneously]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pedestriansCanCross Context triple: [Shibuya Crossing, pedestriansCanCross, inAllDirectionsSimultaneously]
-
A.
pedestrianOnly
Indicates that a path, area, or route is designated exclusively for pedestrians and prohibits vehicle access.
-
B.
pedestrianFriendly
Indicates that an environment, route, or area is designed or suitable for safe, comfortable, and convenient use by pedestrians.
-
C.
hasPedestrianTrafficLevel
Indicates the level or intensity of pedestrian traffic associated with a given location or pathway.
-
D.
hasPedestrianArea
Indicates that a location or zone includes a designated area intended for pedestrian use only or primarily.
-
E.
hasPedestrianPlazaOn
Indicates that a pedestrian plaza is located on, or directly associated with, a specified surface, structure, or area.
- F. None of above. chosen
Provenance (4 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_69a49428d4448190b3b36991ceae87ce |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9c21c2c8190a34d91a7afed23a9 |
completed | March 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69a4b7472c848190b0643872f67084a2 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7da38888190a118ef20ce4ae9aa |
completed | March 1, 2026, 10:04 p.m. |
Created at: March 1, 2026, 7:43 p.m.