Triple
T4451275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Centro de Estudios Latinoamericanos Rómulo Gallegos |
E97612
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
CELARG
CELARG is a Venezuelan cultural and research institution dedicated to promoting Latin American literature, thought, and the legacy of writer Rómulo Gallegos.
|
E439176
|
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: CELARG | Statement: [Centro de Estudios Latinoamericanos Rómulo Gallegos, abbreviation, CELARG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CELARG Context triple: [Centro de Estudios Latinoamericanos Rómulo Gallegos, abbreviation, CELARG]
-
A.
Cellese
Cellese is a regional dialect of the Franco-Provençal language traditionally spoken in a specific area of the Franco-Provençal linguistic region.
-
B.
CARL
CARL is an organization or research group associated with York University, likely focused on a specialized academic or scientific domain.
-
C.
Cesca
Cesca is a feminine given name, commonly used as a short form of Francesca.
-
D.
Clevsin
Clevsin is the ancient Etruscan name for the Italian town of Chiusi, a significant center of Etruscan civilization in central Italy.
-
E.
CESAER
CESAER is a European association of leading universities of science and technology that collaborates to advance engineering education, research, and innovation.
- 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: CELARG Triple: [Centro de Estudios Latinoamericanos Rómulo Gallegos, abbreviation, CELARG]
Generated description
CELARG is a Venezuelan cultural and research institution dedicated to promoting Latin American literature, thought, and the legacy of writer Rómulo Gallegos.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CELARG Target entity description: CELARG is a Venezuelan cultural and research institution dedicated to promoting Latin American literature, thought, and the legacy of writer Rómulo Gallegos.
-
A.
Cellese
Cellese is a regional dialect of the Franco-Provençal language traditionally spoken in a specific area of the Franco-Provençal linguistic region.
-
B.
CARL
CARL is an organization or research group associated with York University, likely focused on a specialized academic or scientific domain.
-
C.
Cesca
Cesca is a feminine given name, commonly used as a short form of Francesca.
-
D.
Clevsin
Clevsin is the ancient Etruscan name for the Italian town of Chiusi, a significant center of Etruscan civilization in central Italy.
-
E.
CESAER
CESAER is a European association of leading universities of science and technology that collaborates to advance engineering education, research, and innovation.
- 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_69b3454777808190b78aa9047ba1f018 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355f3731c81909cc5a782b12ddd38 |
completed | March 13, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6138b6c8c8190a21ad00fb230c0f0 |
completed | March 15, 2026, 2:03 a.m. |
| NEDg | Description generation | batch_69b61464b0dc81909cab007115435b8b |
completed | March 15, 2026, 2:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b6151440648190bf8c1c95e20caf13 |
completed | March 15, 2026, 2:10 a.m. |
Created at: March 12, 2026, 11:33 p.m.