Triple
T32476320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tobu Group |
E829984
|
entity |
| Predicate | hospitalityBusinessType |
P43750
|
FINISHED |
| Object | hotels |
—
|
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: hotels | Statement: [Tobu Group, hospitalityBusinessType, hotels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hospitalityBusinessType Context triple: [Tobu Group, hospitalityBusinessType, hotels]
-
A.
hospitalityContext
Indicates a situational or environmental setting in which hospitality-related interactions, services, or behaviors occur.
-
B.
venueConcept
Indicates a relationship where a venue is associated with, characterized by, or defined in terms of a particular concept or thematic idea.
-
C.
hasHotelType
Indicates that a hotel is classified as belonging to a specific type or category (e.g., resort, boutique, hostel).
-
D.
hotelCategory
Indicates the classification or rating level assigned to a hotel (e.g., star rating or category tier).
-
E.
venueTypeOperated
chosen
Indicates that an entity operates or manages a venue of a specified type.
- 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_69f3491ff3b48190b50a7fa00bb05b1f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c3913f108190b2e10106534b6392 |
completed | May 3, 2026, 3:40 a.m. |
| PD | Predicate disambiguation | batch_69f6ba700a708190ab6db62791e43774 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:58 a.m.