Triple
T16517921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cinema Impero |
E401232
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Asmara |
E92266
|
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: Asmara | Statement: [Cinema Impero, location, Asmara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asmara Context triple: [Cinema Impero, location, Asmara]
-
A.
Asmara
chosen
Asmara is the largest city of Eritrea, known for its well-preserved Italian colonial modernist architecture and status as a UNESCO World Heritage Site.
-
B.
Massawa
Massawa is a historic Eritrean port city on the Red Sea, known for its strategic maritime location and Ottoman- and Italian-influenced architecture.
-
C.
Mekele
Mekele is the capital city of Ethiopia’s Tigray Region and a major political, economic, and cultural center in the country’s north.
-
D.
Awasa
Awasa is a city in southern Ethiopia, known as the capital of the Sidama Region and a hub by Lake Awasa.
-
E.
Djibouti City
Djibouti City is the largest urban center and main economic, political, and cultural hub of the Republic of Djibouti, located on the Gulf of Tadjoura in the Horn of Africa.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e7da2248190a540a5ef8686963d |
completed | April 18, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c291e2008190b41a989c5c6e2860 |
completed | May 10, 2026, 5:38 p.m. |
Created at: April 10, 2026, 5:14 a.m.