Triple
T26877000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shuto Expressway Inner Circular Route |
E676778
|
entity |
| Predicate | encirclesArea |
P43477
|
FINISHED |
| Object | Tokyo city center |
—
|
NE NERFINISHED |
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: Tokyo city center | Statement: [Shuto Expressway Inner Circular Route, encirclesArea, Tokyo city center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: encirclesArea Context triple: [Shuto Expressway Inner Circular Route, encirclesArea, Tokyo city center]
-
A.
enclosesArea
chosen
Indicates that one entity surrounds and contains a bounded region of space occupied or defined by another.
-
B.
coreAreaOf
Indicates that one entity is the central, primary, or most important area or domain of focus for another entity.
-
C.
includesAreaOf
Indicates that one entity encompasses or contains the spatial extent or area covered by another entity.
-
D.
partlyEncircles
Indicates that one entity surrounds another along a substantial but incomplete portion of its boundary or perimeter.
-
E.
areaApprox
Indicates that one entity’s area is approximately equal to the area of another entity.
- 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_69eee9bb44988190b6e11652d028bc59 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61fd623bc819091df736cf3419b99 |
completed | May 2, 2026, 4:01 p.m. |
| PD | Predicate disambiguation | batch_69f61b3d23f481908dfec27adace900a |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 5:36 a.m.