Triple
T7957444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uğur Dündar |
E184774
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Star TV |
E86241
|
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: Star TV | Statement: [Uğur Dündar, employer, Star TV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Star TV Context triple: [Uğur Dündar, employer, Star TV]
-
A.
Star TV
chosen
Star TV is a major Asian satellite television network known for its broad entertainment and news programming across multiple countries.
-
B.
Orange TV
Orange TV is a subscription-based television platform operated by the telecommunications company Orange, offering a range of live channels and on-demand content.
-
C.
Vijay TV
Vijay TV is a popular Tamil-language television channel in India known for its entertainment shows, reality programs, and serials.
-
D.
We TV
We TV is an American cable television network known for its reality programming focused on relationships, family life, and pop culture.
-
E.
TVS Television Network
TVS Television Network was an American syndicated sports television network known for broadcasting a wide range of live sporting events and special programming from the 1960s through the 1980s.
- 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_69ca8293a2388190aace944d7ed9c0c0 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b7ebb24819094bc011d51ef63fb |
completed | March 31, 2026, 3:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe072ef4c8190a8e078c5280913db |
completed | March 31, 2026, 2:55 p.m. |
Created at: March 30, 2026, 5:11 p.m.