Triple
T11059550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Habaguanex S.A. |
E261468
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
Habaguanex
Habaguanex is a Cuban tourism and hospitality company known for operating hotels, restaurants, and shops in Old Havana.
|
E902813
|
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: Habaguanex | Statement: [Habaguanex S.A., abbreviation, Habaguanex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Habaguanex Context triple: [Habaguanex S.A., abbreviation, Habaguanex]
-
A.
Pasochoa
Pasochoa is an extinct volcanic mountain in Ecuador known for its lush cloud forests and rich biodiversity within a protected ecological reserve.
-
B.
Catamayo
Catamayo is a significant urban center in southern Ecuador known for its agricultural production and proximity to the city of Loja.
-
C.
Maragondon
Maragondon is a historic rural municipality in the province of Cavite in the Philippines, known for its Spanish-era heritage sites and nearby natural attractions.
-
D.
Buruanga
Buruanga is a coastal municipality in the province of Aklan in the Philippines, known for its scenic beaches and proximity to the tourist island of Boracay.
-
E.
Kaxuyana
Kaxuyana is an indigenous language variety spoken by the Kaxuyana people of northern Brazil, closely related to other Cariban languages of the 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: Habaguanex Triple: [Habaguanex S.A., abbreviation, Habaguanex]
Generated description
Habaguanex is a Cuban tourism and hospitality company known for operating hotels, restaurants, and shops in Old Havana.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Habaguanex Target entity description: Habaguanex is a Cuban tourism and hospitality company known for operating hotels, restaurants, and shops in Old Havana.
-
A.
Pasochoa
Pasochoa is an extinct volcanic mountain in Ecuador known for its lush cloud forests and rich biodiversity within a protected ecological reserve.
-
B.
Catamayo
Catamayo is a significant urban center in southern Ecuador known for its agricultural production and proximity to the city of Loja.
-
C.
Maragondon
Maragondon is a historic rural municipality in the province of Cavite in the Philippines, known for its Spanish-era heritage sites and nearby natural attractions.
-
D.
Buruanga
Buruanga is a coastal municipality in the province of Aklan in the Philippines, known for its scenic beaches and proximity to the tourist island of Boracay.
-
E.
Kaxuyana
Kaxuyana is an indigenous language variety spoken by the Kaxuyana people of northern Brazil, closely related to other Cariban languages of the 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d798a4f3f88190a29710f64cef9d25 |
completed | April 9, 2026, 12:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3c87ab0308190a6a6ada1708f0ec2 |
completed | April 18, 2026, 6:07 p.m. |
| NEDg | Description generation | batch_69e3cefc00148190a1850dc6e31523c3 |
completed | April 18, 2026, 6:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3d014a644819092c76aa02b573ca9 |
completed | April 18, 2026, 6:40 p.m. |
Created at: April 8, 2026, 9:26 p.m.