Triple
T15828858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Disconnected |
E383814
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Selim Işık |
E387936
|
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: Selim Işık | Statement: [The Disconnected, hasCharacter, Selim Işık]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Selim Işık Context triple: [The Disconnected, hasCharacter, Selim Işık]
-
A.
Selim Işık
chosen
Selim Işık is a central, tragicomic character in Oğuz Atay’s novel "Tutunamayanlar," symbolizing the alienated intellectual who cannot adapt to modern Turkish society.
-
B.
İsmail Selçuk
İsmail Selçuk is a person notable enough to be recognized as a prominent bearer of the Turkish surname Selçuk.
-
C.
Mehmet Ragif
Mehmet Ragif is the birth name of Mehmet Akif Ersoy, the renowned Turkish poet, writer, and author of the Turkish National Anthem.
-
D.
Mehmet Selçuk
Mehmet Selçuk is a Turkish professional footballer known for playing as a midfielder in Turkey’s top leagues.
-
E.
Mustafa Râkim
Mustafa Râkim was a preeminent Ottoman calligrapher renowned for refining and perfecting the sülüs and celî scripts, profoundly influencing the classical tradition of Islamic calligraphy.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e11e62aba8819090978801f4df73fe |
completed | April 16, 2026, 5:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb03ac77081908f2b169d7d26b318 |
completed | May 9, 2026, 10:07 p.m. |
Created at: April 10, 2026, 4:49 a.m.