Triple
T6022950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diez de Octubre municipality |
E134106
|
entity |
| Predicate | hasNeighborhood |
P40
|
FINISHED |
| Object |
Luyanó
Luyanó is a traditional working-class neighborhood in Havana, Cuba, known for its dense urban fabric and vibrant local culture.
|
E565287
|
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: Luyanó | Statement: [Diez de Octubre municipality, hasNeighborhood, Luyanó]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luyanó Context triple: [Diez de Octubre municipality, hasNeighborhood, Luyanó]
-
A.
Lunahuaná
Lunahuaná is a popular Peruvian town known for its adventure tourism, especially whitewater rafting, and its production of pisco and wine in the Cañete Valley.
-
B.
Cailungo
Cailungo is a locality within the municipality of Serravalle in the Republic of San Marino.
-
C.
Lymari
Lymari is a Puerto Rican actress and film producer best known for her roles in movies such as "American Gangster" and "Battlestar Galactica: The Plan."
-
D.
Nolana
Nolana is a genus of flowering plants native mainly to coastal regions of South America, known for their showy, often blue, funnel-shaped blossoms.
-
E.
Yanaon
Yanaon is the former name of Yanam, a small coastal town in India that was once part of French India and retains a distinct Franco-Indian cultural heritage.
- 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: Luyanó Triple: [Diez de Octubre municipality, hasNeighborhood, Luyanó]
Generated description
Luyanó is a traditional working-class neighborhood in Havana, Cuba, known for its dense urban fabric and vibrant local culture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Luyanó Target entity description: Luyanó is a traditional working-class neighborhood in Havana, Cuba, known for its dense urban fabric and vibrant local culture.
-
A.
Lunahuaná
Lunahuaná is a popular Peruvian town known for its adventure tourism, especially whitewater rafting, and its production of pisco and wine in the Cañete Valley.
-
B.
Cailungo
Cailungo is a locality within the municipality of Serravalle in the Republic of San Marino.
-
C.
Lymari
Lymari is a Puerto Rican actress and film producer best known for her roles in movies such as "American Gangster" and "Battlestar Galactica: The Plan."
-
D.
Nolana
Nolana is a genus of flowering plants native mainly to coastal regions of South America, known for their showy, often blue, funnel-shaped blossoms.
-
E.
Yanaon
Yanaon is the former name of Yanam, a small coastal town in India that was once part of French India and retains a distinct Franco-Indian cultural heritage.
- 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_69c008742a5c8190b9cb9c2787a3d8b3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04fbd7978819085d683578bc62aa3 |
completed | March 22, 2026, 8:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1136da26081909b753fa8a2a91084 |
completed | March 23, 2026, 10:18 a.m. |
| NEDg | Description generation | batch_69c1174ff40c8190b19011a46eadea70 |
completed | March 23, 2026, 10:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c117a46d3881908267431287814acd |
completed | March 23, 2026, 10:36 a.m. |
Created at: March 22, 2026, 4:07 p.m.