Triple
T3146533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TUI Group (historical) |
E65777
|
entity |
| Predicate | beganDiversificationIntoTourism |
P46376
|
FINISHED |
| Object | 1990s |
—
|
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: 1990s | Statement: [TUI Group (historical), beganDiversificationIntoTourism, 1990s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: beganDiversificationIntoTourism Context triple: [TUI Group (historical), beganDiversificationIntoTourism, 1990s]
-
A.
hasTourismIndustry
Indicates that a place or region possesses an established tourism industry, involving organized services and activities catering to visitors and travelers.
-
B.
hasTourismImpactOn
Indicates that one entity affects or influences the tourism levels, patterns, or attractiveness of another entity.
-
C.
tourismImportance
Indicates the degree to which a place or entity is significant or valuable as a destination or attraction for tourists.
-
D.
tourismFrom
Indicates that tourists or visitor activity originates from one place and is directed toward another location.
-
E.
tourismType
Indicates the specific category or kind of tourism activity or experience associated with an entity.
- 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_69ad8582f564819088c27e1f96153938 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada598ccf08190b8817c456f38f2d7 |
completed | March 8, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69ad9dfa3d9081908425aa636bb9b897 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada148e9108190b363dd0f1a94ac8e |
completed | March 8, 2026, 4:18 p.m. |
Created at: March 8, 2026, 3:05 p.m.