Triple
T14412206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pablo Berger |
E357356
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object | Torremolinos 73 |
E1098205
|
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: Torremolinos 73 | Statement: [Pablo Berger, directed, Torremolinos 73]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Torremolinos 73 Context triple: [Pablo Berger, directed, Torremolinos 73]
-
A.
Torremolinos 73
chosen
Torremolinos 73 is a Spanish dark comedy film that follows a door-to-door encyclopedia salesman who becomes an unlikely pornographic filmmaker in 1970s Spain.
-
B.
Torremolinos
Torremolinos is a popular seaside resort town on Spain’s Costa del Sol, known for its beaches, nightlife, and tourism-focused economy.
-
C.
Benalmádena
Benalmádena is a coastal resort town on Spain’s Costa del Sol, known for its beaches, marina, and tourist attractions near Málaga.
-
D.
Torremolinos, Spain
Torremolinos, Spain is a popular resort town on the Costa del Sol known for its Mediterranean beaches, vibrant nightlife, and tourism-focused economy.
-
E.
Estepona
Estepona is a coastal resort town on Spain’s Costa del Sol, known for its Mediterranean beaches, marina, and whitewashed old town.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90cb3c708190822f5506ebf7ee9d |
completed | April 14, 2026, 7:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bc79c088190b6fd2984515976d7 |
completed | May 8, 2026, 3:43 a.m. |
Created at: April 10, 2026, 1:17 a.m.