Triple
T8563336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virgin Hotels |
E202740
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | W Hotels |
E242123
|
NE 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: W Hotels | Statement: [Virgin Hotels, competitor, W Hotels]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: W Hotels Context triple: [Virgin Hotels, competitor, W Hotels]
-
A.
W Hotels
chosen
W Hotels is a global luxury lifestyle hotel chain known for its stylish design, vibrant social scene, and contemporary, boutique-inspired accommodations.
-
B.
U Hotels
U Hotels is a hotel brand operated by the Fattal Hotel Group, offering contemporary accommodations and hospitality services.
-
C.
Joie de Vivre Hotels
Joie de Vivre Hotels is a boutique hotel brand known for its eclectic, locally inspired properties and distinctive, playful design.
-
D.
Kimpton
Kimpton is a rural civil parish and village in Hampshire, England, known for its historic church and countryside setting.
-
E.
Kimpton
Kimpton is a small rural village and civil parish in Hertfordshire, England, known for its historic church and traditional English countryside setting.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca8326e6c881908ff720d6abaebdc5 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe9cfc4a48190ae4530d3614d115f |
completed | March 31, 2026, 3:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce895f91bc819099b1b2df59374403 |
completed | April 2, 2026, 3:21 p.m. |
Created at: March 30, 2026, 6:20 p.m.