Triple
T38152997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tunica-Biloxi Tribe of Louisiana |
E952805
|
entity |
| Predicate | operatesCasino |
P66934
|
FINISHED |
| Object | Paragon Casino Resort |
E947481
|
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: Paragon Casino Resort | Statement: [Tunica-Biloxi Tribe of Louisiana, operatesCasino, Paragon Casino Resort]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesCasino Context triple: [Tunica-Biloxi Tribe of Louisiana, operatesCasino, Paragon Casino Resort]
-
A.
hasCasino
Indicates that an entity includes, contains, or is associated with a casino facility or gambling establishment.
-
B.
operatedGame
Indicates that an entity has operated, controlled, or run a particular game.
-
C.
hasSlotMachines
Indicates that an entity contains, offers, or is equipped with one or more slot machines.
-
D.
associatedWithCasino
chosen
Indicates a relationship where an entity has a connection or involvement with a casino, such as through ownership, operation, affiliation, or regular activity.
-
E.
casinoWebsite
Indicates that one entity is a website whose primary function is to offer casino-related gambling or betting services to users.
- F. None of above.
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_69f76f0a67f4819080c492f61d688fcc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a034ca1a8d88190bd44f33814436e59 |
completed | May 12, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41a7d1e1488190b5ceeaa86f85bd76 |
completed | June 28, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_6a034b591f2481908e05562841c9a3c2 |
completed | May 12, 2026, 3:46 p.m. |
Created at: May 3, 2026, 4:21 p.m.