Triple
T2667967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MGM Grand (licensing of brand to casinos and hotels) |
E55682
|
entity |
| Predicate | licenseScope |
P41559
|
FINISHED |
| Object | global |
—
|
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: global | Statement: [MGM Grand (licensing of brand to casinos and hotels), licenseScope, global]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: licenseScope Context triple: [MGM Grand (licensing of brand to casinos and hotels), licenseScope, global]
-
A.
license
Indicates that one entity has granted another entity formal permission or authorization to use, perform, or exploit something under specified terms.
-
B.
licenseFor
Indicates that one entity grants or holds formal permission or authorization for another entity to perform an activity, use a resource, or operate under specified conditions.
-
C.
licenseModel
Indicates the licensing scheme or framework that governs how something may be used, distributed, or accessed.
-
D.
licenseStewardship
Indicates that one entity is responsible for managing, overseeing, or administering a license on behalf of another entity.
-
E.
licensePreference
Indicates a party’s chosen or prioritized type of license to use, grant, or operate under in a given context.
- 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_69ab49e54de48190be708cd1cf8be073 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd98a4ee88190aa7ef914e316ba31 |
completed | March 7, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69abd8190ad481908f3e14ac84d0940a |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd8f98c348190a68064c565589459 |
completed | March 7, 2026, 7:51 a.m. |
Created at: March 6, 2026, 9:54 p.m.