Triple
T7436838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cold Mountain |
E171636
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Gabriel Yared |
E48047
|
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: Gabriel Yared | Statement: [Cold Mountain, musicBy, Gabriel Yared]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gabriel Yared Context triple: [Cold Mountain, musicBy, Gabriel Yared]
-
A.
Gabriel Yared
chosen
Gabriel Yared is a Lebanese-French composer renowned for his evocative film scores, including his Academy Award–winning work on "The English Patient."
-
B.
Walid Guirguis
Walid Guirguis is a screenwriter best known for his work on the 1951 film "M."
-
C.
Firas Tlass
Firas Tlass is a Syrian businessman and member of the prominent Tlass family, known for his connections to the country’s political and economic elite.
-
D.
Omar Razzaz
Omar Razzaz is a Jordanian politician and economist who served as the country’s prime minister from 2018 to 2020, known for his focus on economic reform and anti-corruption measures.
-
E.
Ali Laarayedh
Ali Laarayedh is a Tunisian politician and former prime minister who played a key role in the country’s post-Arab Spring transitional government.
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f349399c8190b46d5882ece2e73a |
completed | March 27, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8278670bc819095bdbcc0837b6716 |
completed | March 28, 2026, 7:09 p.m. |
Created at: March 27, 2026, 3:13 p.m.