Triple
T11769324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gregory La Cava |
E279856
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
La Cava
La Cava is a surname most notably associated with American film director Gregory La Cava, known for his influential work in early 20th-century cinema.
|
E1003802
|
NE FINISHED |
How this triple was built (4 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: La Cava | Statement: [Gregory La Cava, familyName, La Cava]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Cava Context triple: [Gregory La Cava, familyName, La Cava]
-
A.
Martorell
Martorell is a town in Catalonia, Spain, known as an important industrial hub within the Barcelona metropolitan area.
-
B.
Banyoles
Banyoles is a town in Catalonia, Spain, best known for its large natural lake and scenic surroundings.
-
C.
Molins de Rei
Molins de Rei is a municipality in the Barcelona metropolitan area of Catalonia, Spain, situated along the Llobregat River.
-
D.
Gavà
Gavà is a coastal municipality in Catalonia, Spain, located near Barcelona and known for its beaches and archaeological heritage.
-
E.
Vilafranca del Penedès
Vilafranca del Penedès is a historic town in Catalonia, Spain, known as a traditional wine-producing center in the Penedès region.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: La Cava Triple: [Gregory La Cava, familyName, La Cava]
Generated description
La Cava is a surname most notably associated with American film director Gregory La Cava, known for his influential work in early 20th-century cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: La Cava Target entity description: La Cava is a surname most notably associated with American film director Gregory La Cava, known for his influential work in early 20th-century cinema.
-
A.
Martorell
Martorell is a town in Catalonia, Spain, known as an important industrial hub within the Barcelona metropolitan area.
-
B.
Banyoles
Banyoles is a town in Catalonia, Spain, best known for its large natural lake and scenic surroundings.
-
C.
Molins de Rei
Molins de Rei is a municipality in the Barcelona metropolitan area of Catalonia, Spain, situated along the Llobregat River.
-
D.
Gavà
Gavà is a coastal municipality in Catalonia, Spain, located near Barcelona and known for its beaches and archaeological heritage.
-
E.
Vilafranca del Penedès
Vilafranca del Penedès is a historic town in Catalonia, Spain, known as a traditional wine-producing center in the Penedès region.
- F. None of above. chosen
Provenance (5 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_69d6ab01d2688190ad8ed6bda487eaa5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a55c9f988190b203b66a28c767ae |
completed | April 10, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68e9b70d08190aa74e612947317b5 |
completed | May 2, 2026, 11:54 p.m. |
| NEDg | Description generation | batch_69f68f8d2ca08190a385635fb6130a9f |
completed | May 2, 2026, 11:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f69033a66481908bf4ae23fced5983 |
completed | May 3, 2026, midnight |
Created at: April 8, 2026, 9:41 p.m.