Triple
T14435913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marriott Bonvoy |
E357959
|
entity |
| Predicate | coversBrand |
P1500
|
FINISHED |
| Object | Westin |
E866620
|
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: Westin | Statement: [Marriott Bonvoy, coversBrand, Westin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Westin Context triple: [Marriott Bonvoy, coversBrand, Westin]
-
A.
Westin
chosen
Westin is an upscale hotel and resort brand known for its wellness-focused amenities, including signature Heavenly Beds and fitness-oriented services.
-
B.
Hilton
Hilton is a village and civil parish in South Derbyshire, England, known for its rapid modern expansion and residential developments.
-
C.
Hilton
Hilton is a global hospitality company that operates a worldwide portfolio of hotels and resorts across multiple brands.
-
D.
Hilton
Hilton is an inner-western suburb of Adelaide in South Australia, known for its proximity to the city centre and mixed residential–commercial character.
-
E.
Hyatt
Hyatt is a surname most notably associated with Alpheus Hyatt, an American zoologist and paleontologist known for his work on evolutionary theory and cephalopods.
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9148cf4481909082cc91b2f76218 |
completed | April 14, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d84fd888190b05dcf9191bae337 |
completed | May 8, 2026, 4:58 a.m. |
Created at: April 10, 2026, 1:18 a.m.