Triple
T9513446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calle 23 (La Rampa) |
E229459
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object | Yara cinema |
E61948
|
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: Yara cinema | Statement: [Calle 23 (La Rampa), hasLandmark, Yara cinema]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yara cinema Context triple: [Calle 23 (La Rampa), hasLandmark, Yara cinema]
-
A.
Yara Cinema
chosen
Yara Cinema is a prominent and historic movie theater in Havana, Cuba, known as a cultural landmark and popular gathering place in the Vedado district.
-
B.
Riama Film
Riama Film is an Italian film production company best known for producing Federico Fellini’s classic 1960 drama "La Dolce Vita."
-
C.
Geria Film
Geria Film is a film production company known for producing the movie "Fedora."
-
D.
Yannai
Yannai is another name for Alexander Jannaeus, a Hasmonean king of Judea and high priest who ruled in the early 1st century BCE.
-
E.
Teitler Film
Teitler Film is a film production company known for producing feature films such as the family sci-fi adventure "Zathura: A Space Adventure."
- 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_69ca84777560819084cddd999badc1aa |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd986aa99c8190b2eaa7f9b111aa2e |
completed | April 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1526fbad8819099dfae3b7226898b |
completed | April 4, 2026, 6:03 p.m. |
Created at: March 30, 2026, 7:58 p.m.