Triple
T5773520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fuji Television Building |
E127383
|
entity |
| Predicate | cityscapeRole |
P8236
|
FINISHED |
| Object | landmark of Odaiba waterfront |
—
|
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: landmark of Odaiba waterfront | Statement: [Fuji Television Building, cityscapeRole, landmark of Odaiba waterfront]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityscapeRole Context triple: [Fuji Television Building, cityscapeRole, landmark of Odaiba waterfront]
-
A.
cityScene
Indicates a scene or setting that takes place within an urban or city environment.
-
B.
urbanRole
Indicates the function, status, or role that an entity holds within an urban or city context.
-
C.
hasCityRole
Indicates that an entity holds or is assigned a specific role, function, or status within a particular city.
-
D.
hasUrbanRole
chosen
Indicates that an entity plays a specific functional or social role within an urban or city context.
-
E.
roleInUrbanPlan
Indicates the specific function, responsibility, or position an entity holds within an urban planning context or scheme.
- F. None of above.
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_69c008361fa88190aefa4dc41b051e7f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02acb12c081908e4beee4a957f9f9 |
completed | March 22, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69c021d0c6088190ba670ddcdbf5ca3e |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:50 p.m.