Triple
T11361153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cinisi |
E269087
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object |
Terrasini
Terrasini is a coastal town in the Metropolitan City of Palermo in Sicily, Italy, known for its beaches, fishing traditions, and proximity to Palermo’s airport.
|
E921337
|
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: Terrasini | Statement: [Cinisi, hasNearbySettlement, Terrasini]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terrasini Context triple: [Cinisi, hasNearbySettlement, Terrasini]
-
A.
Tordino
Tordino is a river in the Abruzzo region of central Italy that flows through the city of Teramo before reaching the Adriatic Sea.
-
B.
Clusone
Clusone is a historic town in northern Italy known for its medieval architecture and frescoes, located in the Lombardy region.
-
C.
Mesoraca
Mesoraca is a town in the Calabria region of southern Italy, historically notable as the birthplace of Pope Zosimus.
-
D.
Cosentia
Cosentia is the ancient Latin name of the city now known as Cosenza in southern Italy, historically an important center of the Bruttii in Calabria.
-
E.
Scordia
Scordia is a town and comune in eastern Sicily, Italy, known for its agricultural production, particularly citrus fruits.
- 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: Terrasini Triple: [Cinisi, hasNearbySettlement, Terrasini]
Generated description
Terrasini is a coastal town in the Metropolitan City of Palermo in Sicily, Italy, known for its beaches, fishing traditions, and proximity to Palermo’s airport.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Terrasini Target entity description: Terrasini is a coastal town in the Metropolitan City of Palermo in Sicily, Italy, known for its beaches, fishing traditions, and proximity to Palermo’s airport.
-
A.
Tordino
Tordino is a river in the Abruzzo region of central Italy that flows through the city of Teramo before reaching the Adriatic Sea.
-
B.
Clusone
Clusone is a historic town in northern Italy known for its medieval architecture and frescoes, located in the Lombardy region.
-
C.
Mesoraca
Mesoraca is a town in the Calabria region of southern Italy, historically notable as the birthplace of Pope Zosimus.
-
D.
Cosentia
Cosentia is the ancient Latin name of the city now known as Cosenza in southern Italy, historically an important center of the Bruttii in Calabria.
-
E.
Scordia
Scordia is a town and comune in eastern Sicily, Italy, known for its agricultural production, particularly citrus fruits.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea442e5c8190babfde25540b27e9 |
completed | April 9, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e556542ecc8190a8109c17944598ab |
completed | April 19, 2026, 10:25 p.m. |
| NEDg | Description generation | batch_69e562bb085c8190942766d12d838798 |
completed | April 19, 2026, 11:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e569f0e6948190b285ca84aca03771 |
completed | April 19, 2026, 11:49 p.m. |
Created at: April 8, 2026, 9:33 p.m.