Triple
T18021961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Wynn |
E431144
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Wynn |
—
|
NE NERFINISHED |
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 | Statement: [Steve Wynn, familyName, Wynn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wynn Context triple: [Steve Wynn, familyName, Wynn]
-
A.
Wynn
chosen
Wynn is a given name that can be used for both males and females, often associated with English or Welsh origins.
-
B.
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.
-
C.
Wynn Palace
Wynn Palace is a luxury integrated resort and casino on the Cotai Strip in Macau, known for its opulent design, high-end amenities, and entertainment offerings.
-
D.
Wynn Macau
Wynn Macau is a luxury hotel and casino resort located on the Macau Peninsula, known for its upscale accommodations, gaming facilities, and entertainment offerings.
-
E.
Harrah
Harrah is a small city in central Oklahoma known for its suburban-rural character and proximity to Oklahoma City.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b9c299c48190b0cceecf77cb6de9 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 10:24 a.m.