Triple
T6045706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hankyu Hanshin Hotels Co., Ltd. |
E134660
|
entity |
| Predicate | areaServedType |
P68386
|
FINISHED |
| Object | domestic |
—
|
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: domestic | Statement: [Hankyu Hanshin Hotels Co., Ltd., areaServedType, domestic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaServedType Context triple: [Hankyu Hanshin Hotels Co., Ltd., areaServedType, domestic]
-
A.
areaServed
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
-
B.
sectorServed
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
-
C.
cityServedType
Indicates the type or category of city that is served by a given entity (such as a facility, service, or infrastructure).
-
D.
hasServiceAreas
Indicates that an entity provides services within, or is operational across, specific geographic or functional areas.
-
E.
geographicAreaOfSupport
Indicates the geographic region or area within which support, assistance, or services are provided or applicable.
- 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_69c00876a69881908088a2626d3b2666 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056e41f98819089c205ba6138faf0 |
completed | March 22, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69c049eb52a08190ac10fd703735f5aa |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8d4a148190bd8f95caae978e1b |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:09 p.m.