Triple
T13781213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TRT |
E331133
|
entity |
| Predicate | operatesRadioStation |
P42386
|
FINISHED |
| Object | TRT Türkü |
E331133
|
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: TRT Türkü | Statement: [TRT, operatesRadioStation, TRT Türkü]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TRT Türkü Context triple: [TRT, operatesRadioStation, TRT Türkü]
-
A.
TRT
TRT is the station code for Tartu railway station, the main rail transport hub in the city of Tartu, Estonia.
-
B.
TRT
chosen
TRT is Turkey's national public broadcaster, operating multiple television and radio channels domestically and internationally.
-
C.
TRT
TRT is the time zone used in Turkey, corresponding to UTC+3.
-
D.
TRT Haber
TRT Haber is a Turkish public television news channel providing national and international news coverage as part of the state broadcaster TRT.
-
E.
TRT Spor
TRT Spor is a Turkish state-owned sports television channel that broadcasts live sporting events, news, and related programming.
- 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02460a688190a27874f8d35819c7 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1b8689c8190b3ef7416000ef89e |
completed | May 6, 2026, 8:16 p.m. |
Created at: April 9, 2026, 10:11 p.m.