Triple
T2834155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Rampa |
E62309
|
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: [La Rampa, hasLandmark, Yara cinema]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yara cinema Context triple: [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.
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."
-
C.
Cinelândia
Cinelândia is a historic and culturally vibrant square in downtown Rio de Janeiro, Brazil, known for its theaters, cinemas, and early 20th-century architecture.
-
D.
Le Cinéma
Le Cinéma is a movie theater within Tokyo’s Bunkamura cultural complex, known for screening a curated selection of domestic and international films.
-
E.
Bay Films
Bay Films is a film production company founded by director Michael Bay, known for producing high-octane action movies and large-scale Hollywood blockbusters.
- 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_69ab4c3c39188190955b9c49d98463d8 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdec18b808190aedae2ed11d53b15 |
completed | March 7, 2026, 8:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe8bf82808190a556e22d518f46f7 |
completed | March 10, 2026, 9:47 a.m. |
Created at: March 6, 2026, 10:01 p.m.