Triple
T23430007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hard Rock Casino |
E563299
|
entity |
| Predicate | operatesUnderBrand |
P6092
|
FINISHED |
| Object | Hard Rock |
—
|
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: Hard Rock | Statement: [Hard Rock Casino, operatesUnderBrand, Hard Rock]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hard Rock Context triple: [Hard Rock Casino, operatesUnderBrand, Hard Rock]
-
A.
Hard Rock
chosen
Hard Rock is a globally recognized entertainment and hospitality brand known for its rock-and-roll–themed restaurants, hotels, casinos, and music memorabilia.
-
B.
Rock
"Rock" is a popular Afrobeats/hip-hop song by Nigerian rapper and singer Olamide, known for its smooth melody and romantic lyrics.
-
C.
Rock
Rock is the original civilian name of Mega Man, the humanoid robot protagonist of Capcom’s classic action-platformer video game series.
-
D.
Rock
Rock is a professional box lacrosse team based in Toronto, Ontario, competing in the National Lacrosse League.
-
E.
Rock
Rock is a small, affluent coastal village in Cornwall, England, known for its sailing, watersports, and popularity as a holiday destination.
- 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_69e24553980c8190bb66a2ae0bdab125 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a5d6d1c881908e3c4ac0e7cd30cd |
completed | April 29, 2026, 6:31 a.m. |
Created at: April 17, 2026, 5:48 p.m.