Triple
T7957445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uğur Dündar |
E184774
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Show TV |
E654077
|
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: Show TV | Statement: [Uğur Dündar, employer, Show TV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Show TV Context triple: [Uğur Dündar, employer, Show TV]
-
A.
Show TV
chosen
Show TV is a major Turkish national television channel known for broadcasting popular entertainment programs, series, and news.
-
B.
We TV
We TV is an American cable television network known for its reality programming focused on relationships, family life, and pop culture.
-
C.
TV Action
TV Action was a British weekly comic magazine known for publishing adventure and science fiction strips based on popular television series.
-
D.
.tv
.tv is the country-code top-level domain originally assigned to Tuvalu that has become popular worldwide for websites related to television and video content.
-
E.
TVING
TVING is a South Korean online streaming platform offering a wide range of domestic films, dramas, and entertainment content.
- 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.