Triple
T2822620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dongo |
E54844
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
Gravedona
Gravedona is a picturesque town on the shores of Lake Como in northern Italy, known for its historic churches and scenic lakeside setting.
|
E301019
|
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: Gravedona | Statement: [Dongo, locatedNear, Gravedona]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gravedona Context triple: [Dongo, locatedNear, Gravedona]
-
A.
Dovadola
Dovadola is a small Italian town and municipality in the Emilia-Romagna region, known for its historic center and scenic location in the Apennine foothills.
-
B.
Valperga
Valperga is a historical novel by Mary Shelley that reimagines the life and times of the 14th-century Italian warlord Castruccio Castracani through a blend of romance, politics, and philosophical reflection.
-
C.
Mora
Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
-
D.
Dausa
Dausa is a town and district headquarters in the Indian state of Rajasthan, known for its historical forts, stepwells, and proximity to Jaipur.
-
E.
Dainzú
Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
- 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: Gravedona Triple: [Dongo, locatedNear, Gravedona]
Generated description
Gravedona is a picturesque town on the shores of Lake Como in northern Italy, known for its historic churches and scenic lakeside setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gravedona Target entity description: Gravedona is a picturesque town on the shores of Lake Como in northern Italy, known for its historic churches and scenic lakeside setting.
-
A.
Dovadola
Dovadola is a small Italian town and municipality in the Emilia-Romagna region, known for its historic center and scenic location in the Apennine foothills.
-
B.
Valperga
Valperga is a historical novel by Mary Shelley that reimagines the life and times of the 14th-century Italian warlord Castruccio Castracani through a blend of romance, politics, and philosophical reflection.
-
C.
Mora
Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
-
D.
Dausa
Dausa is a town and district headquarters in the Indian state of Rajasthan, known for its historical forts, stepwells, and proximity to Jaipur.
-
E.
Dainzú
Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
- 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_69ab49e100c0819082a40cb797383243 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde71fdc08190b18660261fe24adf |
completed | March 7, 2026, 8:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afceaa45e88190a9007885cf7868ef |
completed | March 10, 2026, 7:56 a.m. |
| NEDg | Description generation | batch_69afcf138c00819087913972df96f5ad |
completed | March 10, 2026, 7:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afcf8d0318819088f9abd895f8ba0a |
completed | March 10, 2026, 8 a.m. |
Created at: March 6, 2026, 9:59 p.m.