Triple
T17765384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vico Equense |
E443488
|
entity |
| Predicate | hasPort |
P35
|
FINISHED |
| Object |
Seiano marina
Seiano marina is a small coastal harbor and seaside area in the Seiano district of Vico Equense on Italy’s Sorrento Peninsula.
|
E1287436
|
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: Seiano marina | Statement: [Vico Equense, hasPort, Seiano marina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seiano marina Context triple: [Vico Equense, hasPort, Seiano marina]
-
A.
Maruim
Maruim is a municipality in the Brazilian state of Sergipe, located along the Sergipe River and known for its historical and regional cultural significance.
-
B.
Sanchica
Sanchica is the fictional daughter of Sancho Panza in Miguel de Cervantes' novel "Don Quixote."
-
C.
Sannomiya
Sannomiya is a major commercial and transportation hub in central Kobe, Japan, known for its shopping streets, nightlife, and role as the city’s downtown core.
-
D.
Makinami
Makinami was a Japanese destroyer of the Imperial Japanese Navy that served in World War II, notably in Pacific naval engagements.
-
E.
Omura
Omura is a coastal city in western Japan known for its proximity to Nagasaki, Omura Bay, and its regional industrial and transportation hubs.
- 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: Seiano marina Triple: [Vico Equense, hasPort, Seiano marina]
Generated description
Seiano marina is a small coastal harbor and seaside area in the Seiano district of Vico Equense on Italy’s Sorrento Peninsula.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Seiano marina Target entity description: Seiano marina is a small coastal harbor and seaside area in the Seiano district of Vico Equense on Italy’s Sorrento Peninsula.
-
A.
Maruim
Maruim is a municipality in the Brazilian state of Sergipe, located along the Sergipe River and known for its historical and regional cultural significance.
-
B.
Sanchica
Sanchica is the fictional daughter of Sancho Panza in Miguel de Cervantes' novel "Don Quixote."
-
C.
Sannomiya
Sannomiya is a major commercial and transportation hub in central Kobe, Japan, known for its shopping streets, nightlife, and role as the city’s downtown core.
-
D.
Makinami
Makinami was a Japanese destroyer of the Imperial Japanese Navy that served in World War II, notably in Pacific naval engagements.
-
E.
Omura
Omura is a coastal city in western Japan known for its proximity to Nagasaki, Omura Bay, and its regional industrial and transportation hubs.
- 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e485fc03e48190a8044e1b40f66f20 |
completed | April 19, 2026, 7:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a02efbf6a4081908399ec1edf6f5a97 |
completed | May 12, 2026, 9:15 a.m. |
| NEDg | Description generation | batch_6a02f113a41c8190b17611eaa50516ca |
completed | May 12, 2026, 9:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a02f1e980f4819087eb191e13396581 |
completed | May 12, 2026, 9:24 a.m. |
Created at: April 10, 2026, 10:11 a.m.