Triple
T13423177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Kaseya |
E313408
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | The Kaseya |
E313408
|
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: The Kaseya | Statement: [The Kaseya, nickname, The Kaseya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Kaseya Context triple: [The Kaseya, nickname, The Kaseya]
-
A.
The Kaseya
chosen
The Kaseya is the commonly used nickname for Kaseya Center, a major indoor sports and entertainment arena in Miami, Florida.
-
B.
Cencibel
Cencibel is a Spanish red wine grape variety, better known internationally as Tempranillo, used to produce full-bodied, age-worthy wines.
-
C.
Cyber Pearl
Cyber Pearl is a prominent commercial office complex in Hyderabad’s HITEC City, known for housing numerous IT and technology companies.
-
D.
Cyber Towers
Cyber Towers is a prominent IT office complex in Hyderabad, India, widely recognized as the iconic gateway building of the HITEC City technology hub.
-
E.
Behind the Cloud
"Behind the Cloud" is a business and leadership book by Salesforce founder Marc Benioff that chronicles the company’s growth and shares strategies for building a successful cloud-based enterprise.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaecf13748190ae40c7b95164f914 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7308493e481909da52f8bbcc0bd6b |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:39 p.m.