Triple
T8309713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sumapaz Province |
E194559
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Silvania
Silvania is a municipality and town in the Cundinamarca Department of Colombia, known for its rural landscapes and proximity to Bogotá.
|
E725060
|
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: Silvania | Statement: [Sumapaz Province, contains, Silvania]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Silvania Context triple: [Sumapaz Province, contains, Silvania]
-
A.
Soline
Soline is a small coastal village on the Croatian island of Krk, known for its tranquil bays and Adriatic seaside setting.
-
B.
Clevsin
Clevsin is the ancient Etruscan name for the Italian town of Chiusi, a significant center of Etruscan civilization in central Italy.
-
C.
Eltigen
Eltigen is a coastal village on the Kerch Peninsula in Crimea, historically notable as a key site of Soviet amphibious landings during World War II.
-
D.
Vacone
Vacone is a small historic hilltop village in the Lazio region of central Italy, known for its scenic countryside and traditional rural character.
-
E.
Travilla
Travilla was an American costume designer best known for creating some of Marilyn Monroe’s most iconic film dresses, including those in "Gentlemen Prefer Blondes."
- 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: Silvania Triple: [Sumapaz Province, contains, Silvania]
Generated description
Silvania is a municipality and town in the Cundinamarca Department of Colombia, known for its rural landscapes and proximity to Bogotá.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Silvania Target entity description: Silvania is a municipality and town in the Cundinamarca Department of Colombia, known for its rural landscapes and proximity to Bogotá.
-
A.
Soline
Soline is a small coastal village on the Croatian island of Krk, known for its tranquil bays and Adriatic seaside setting.
-
B.
Clevsin
Clevsin is the ancient Etruscan name for the Italian town of Chiusi, a significant center of Etruscan civilization in central Italy.
-
C.
Eltigen
Eltigen is a coastal village on the Kerch Peninsula in Crimea, historically notable as a key site of Soviet amphibious landings during World War II.
-
D.
Vacone
Vacone is a small historic hilltop village in the Lazio region of central Italy, known for its scenic countryside and traditional rural character.
-
E.
Travilla
Travilla was an American costume designer best known for creating some of Marilyn Monroe’s most iconic film dresses, including those in "Gentlemen Prefer Blondes."
- 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_69ca82e613e88190bf8139669bbd0d53 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f2d2c30819095075940479b75a7 |
completed | March 31, 2026, 8 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd95665390819089c8becad018cf51 |
completed | April 1, 2026, 10 p.m. |
| NEDg | Description generation | batch_69cda62070888190b55b3f54d29e28e7 |
completed | April 1, 2026, 11:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cdb21a65d88190a19dd41f95d173c8 |
completed | April 2, 2026, 12:02 a.m. |
Created at: March 30, 2026, 5:54 p.m.