Triple
T11308898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Trapani |
E267786
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Santa Ninfa
Santa Ninfa is a small town in western Sicily, Italy, known for its agricultural economy and its reconstruction after being heavily damaged by the 1968 Belice earthquake.
|
E917263
|
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: Santa Ninfa | Statement: [Province of Trapani, contains, Santa Ninfa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Ninfa Context triple: [Province of Trapani, contains, Santa Ninfa]
-
A.
Pamona
Pamona is an Austronesian language spoken by the Pamona people of Central Sulawesi, Indonesia.
-
B.
Corinna
Corinna was an ancient Greek lyric poet from Boeotia, renowned for her choral poetry composed in the Aeolic dialect.
-
C.
Sylvana
Sylvana is a feminine given name, often considered a variant of Silvana, typically associated with meanings related to forests or woodland.
-
D.
Marisus
Marisus is the historical Latin name for the Mureș River, a major waterway flowing through present-day Romania and Hungary.
-
E.
Clorinda
Clorinda is a border city in northeastern Argentina’s Formosa Province, located opposite Asunción, Paraguay, and serving as an important regional commercial and transport hub.
- 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: Santa Ninfa Triple: [Province of Trapani, contains, Santa Ninfa]
Generated description
Santa Ninfa is a small town in western Sicily, Italy, known for its agricultural economy and its reconstruction after being heavily damaged by the 1968 Belice earthquake.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Santa Ninfa Target entity description: Santa Ninfa is a small town in western Sicily, Italy, known for its agricultural economy and its reconstruction after being heavily damaged by the 1968 Belice earthquake.
-
A.
Pamona
Pamona is an Austronesian language spoken by the Pamona people of Central Sulawesi, Indonesia.
-
B.
Corinna
Corinna was an ancient Greek lyric poet from Boeotia, renowned for her choral poetry composed in the Aeolic dialect.
-
C.
Sylvana
Sylvana is a feminine given name, often considered a variant of Silvana, typically associated with meanings related to forests or woodland.
-
D.
Marisus
Marisus is the historical Latin name for the Mureș River, a major waterway flowing through present-day Romania and Hungary.
-
E.
Clorinda
Clorinda is a border city in northeastern Argentina’s Formosa Province, located opposite Asunción, Paraguay, and serving as an important regional commercial and transport hub.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9bf87d88190904c2d174578ebbf |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50a70022081908bc74185003a3503 |
completed | April 19, 2026, 5:01 p.m. |
| NEDg | Description generation | batch_69e510fb1e288190a7a38fe896d7b91d |
completed | April 19, 2026, 5:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e516bec3e481909cbd0d9c683d2191 |
completed | April 19, 2026, 5:54 p.m. |
Created at: April 8, 2026, 9:32 p.m.