Triple
T3237119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taxi to the Dark Side |
E67880
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Ilan Eshkeri |
E126637
|
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: Ilan Eshkeri | Statement: [Taxi to the Dark Side, musicBy, Ilan Eshkeri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ilan Eshkeri Context triple: [Taxi to the Dark Side, musicBy, Ilan Eshkeri]
-
A.
Ilan Eshkeri
chosen
Ilan Eshkeri is a British composer known for his orchestral film scores and collaborations on movies, television, and video games.
-
B.
Doron Peled
Doron Peled is a computer scientist known for his contributions to formal methods and model checking, particularly in collaboration with Edmund M. Clarke.
-
C.
Dov Moran
Dov Moran is an Israeli entrepreneur and inventor best known as the creator of the USB flash drive and a pioneer in the flash memory industry.
-
D.
Yoav Nir
Yoav Nir is a computer scientist and cryptography expert known for his work on internet security standards, including co-authoring RFC 7539 on the ChaCha20 and Poly1305 encryption algorithms.
-
E.
Dov Karmi
Dov Karmi was a prominent Israeli architect known for helping shape the modernist architectural landscape of Tel Aviv and other parts of Israel in the mid-20th century.
- 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_69ad858d27348190abb61c280b4c86a9 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaef29bf48190a9aa3a39f0138428 |
completed | March 8, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b277459d1081909766934ce6a56091 |
completed | March 12, 2026, 8:20 a.m. |
Created at: March 8, 2026, 3:08 p.m.