Triple
T19386041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Vibo Valentia |
E484935
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Parghelia
Parghelia is a coastal town in the Calabria region of southern Italy, known for its beaches and proximity to the popular resort of Tropea.
|
E1377780
|
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: Parghelia | Statement: [Province of Vibo Valentia, contains, Parghelia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Parghelia Context triple: [Province of Vibo Valentia, contains, Parghelia]
-
A.
Daryapur
Daryapur is a town in the Amravati district of Maharashtra, India, known for its agricultural economy and regional market activities.
-
B.
Ishwarpur
Ishwarpur is a municipality-level city located in Nepal’s Madhesh Province.
-
C.
Sikandarpur
Sikandarpur is a metro station in the Delhi Metro network that serves the Gurugram area and provides an interchange with the Rapid Metro system.
-
D.
Dadri
Dadri is a town in the Indian state of Uttar Pradesh known for its industrial development and proximity to the National Capital Region.
-
E.
Sheohar
Sheohar is a town in the Indian state of Bihar that serves as an administrative and commercial center for the surrounding rural region.
- 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: Parghelia Triple: [Province of Vibo Valentia, contains, Parghelia]
Generated description
Parghelia is a coastal town in the Calabria region of southern Italy, known for its beaches and proximity to the popular resort of Tropea.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Parghelia Target entity description: Parghelia is a coastal town in the Calabria region of southern Italy, known for its beaches and proximity to the popular resort of Tropea.
-
A.
Daryapur
Daryapur is a town in the Amravati district of Maharashtra, India, known for its agricultural economy and regional market activities.
-
B.
Ishwarpur
Ishwarpur is a municipality-level city located in Nepal’s Madhesh Province.
-
C.
Sikandarpur
Sikandarpur is a metro station in the Delhi Metro network that serves the Gurugram area and provides an interchange with the Rapid Metro system.
-
D.
Dadri
Dadri is a town in the Indian state of Uttar Pradesh known for its industrial development and proximity to the National Capital Region.
-
E.
Sheohar
Sheohar is a town in the Indian state of Bihar that serves as an administrative and commercial center for the surrounding rural region.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b40d1148190b4fcd9ad56aa6910 |
completed | April 20, 2026, 12:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07404041288190b8b76ea6f4209636 |
completed | May 15, 2026, 3:48 p.m. |
| NEDg | Description generation | batch_6a0740d489988190bf12f8515934e811 |
completed | May 15, 2026, 3:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07416b52888190aa6b2a251b407abd |
completed | May 15, 2026, 3:53 p.m. |
Created at: April 10, 2026, 1:35 p.m.