Triple
T10272079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephen Wynn |
E240861
|
entity |
| Predicate | founded |
P104
|
FINISHED |
| Object | Wynn Resorts |
E26370
|
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: Wynn Resorts | Statement: [Stephen Wynn, founded, Wynn Resorts]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wynn Resorts Context triple: [Stephen Wynn, founded, Wynn Resorts]
-
A.
Wynn Resorts
chosen
Wynn Resorts is a luxury hotel and casino development company known for its high-end integrated resorts in Las Vegas and Macau.
-
B.
Las Vegas Sands
Las Vegas Sands is a major global casino and resort company known for its large-scale integrated resorts in Las Vegas and Asia.
-
C.
MGM Resorts International
MGM Resorts International is a major global hospitality and entertainment company known for operating numerous high-profile casino resorts and hotels, particularly on the Las Vegas Strip.
-
D.
Wynn Las Vegas
Wynn Las Vegas is a luxury resort and casino on the Las Vegas Strip known for its upscale accommodations, fine dining, and high-end entertainment and shopping.
-
E.
Wynn
Wynn is a given name that can be used for both males and females, often associated with English or Welsh origins.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2872830819080fdfa816167d04c |
completed | April 7, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71ceeeec88190a36a5e67dc44cfe1 |
completed | April 9, 2026, 3:28 a.m. |
Created at: April 6, 2026, 11:36 a.m.