Triple
T2828157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyoto Municipal Subway |
E54972
|
entity |
| Predicate | hasDirectionCoverage |
P15156
|
FINISHED |
| Object | north–south |
—
|
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: north–south | Statement: [Kyoto Municipal Subway, hasDirectionCoverage, north–south]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDirectionCoverage Context triple: [Kyoto Municipal Subway, hasDirectionCoverage, north–south]
-
A.
hasCoverage
Indicates that one entity provides insurance or protection coverage for another entity or subject.
-
B.
containsDirectionOf
Indicates that one entity includes or encompasses the directional orientation or path associated with another entity.
-
C.
hasDirectionType
Indicates that something possesses or is associated with a specific type or category of direction.
-
D.
hasRouteDirection
chosen
Indicates that a specified route is associated with a particular travel direction (e.g., inbound, outbound, northbound).
-
E.
hasDirectionVariability
Indicates that the direction associated with an entity or process is not fixed but varies over time, space, or conditions.
- 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_69ab49e100c0819082a40cb797383243 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde95d8148190bcae8b0659a5c116 |
completed | March 7, 2026, 8:15 a.m. |
| PD | Predicate disambiguation | batch_69abdd0acab881909e8c25cbef83678c |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:59 p.m.