Triple
T13164121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Collegno |
E312801
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object |
Pianezza
Pianezza is a municipality in the Metropolitan City of Turin in Italy’s Piedmont region, situated in the suburban area northwest of Turin.
|
E1023639
|
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: Pianezza | Statement: [Collegno, borderedBy, Pianezza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pianezza Context triple: [Collegno, borderedBy, Pianezza]
-
A.
Pianiga
Pianiga is a municipality in the Veneto region of northeastern Italy, situated on the mainland near Venice.
-
B.
Piana
Piana is a picturesque coastal village in western Corsica, France, renowned for its dramatic red granite cliffs and proximity to the UNESCO-listed Gulf of Porto and Calanche de Piana.
-
C.
Marpi plain
Marpi plain is a broad, low-lying area on Saipan in the Northern Mariana Islands, known for its proximity to historic World War II sites such as Suicide Cliff.
-
D.
Porlezza
Porlezza is a picturesque lakeside town in northern Italy’s Lombardy region, known for its scenic setting on the eastern end of Lake Lugano near the Swiss border.
-
E.
Planas
Planas is a municipal barrio (district) of the town of Aibonito in Puerto Rico.
- 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: Pianezza Triple: [Collegno, borderedBy, Pianezza]
Generated description
Pianezza is a municipality in the Metropolitan City of Turin in Italy’s Piedmont region, situated in the suburban area northwest of Turin.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pianezza Target entity description: Pianezza is a municipality in the Metropolitan City of Turin in Italy’s Piedmont region, situated in the suburban area northwest of Turin.
-
A.
Pianiga
Pianiga is a municipality in the Veneto region of northeastern Italy, situated on the mainland near Venice.
-
B.
Piana
Piana is a picturesque coastal village in western Corsica, France, renowned for its dramatic red granite cliffs and proximity to the UNESCO-listed Gulf of Porto and Calanche de Piana.
-
C.
Marpi plain
Marpi plain is a broad, low-lying area on Saipan in the Northern Mariana Islands, known for its proximity to historic World War II sites such as Suicide Cliff.
-
D.
Porlezza
Porlezza is a picturesque lakeside town in northern Italy’s Lombardy region, known for its scenic setting on the eastern end of Lake Lugano near the Swiss border.
-
E.
Planas
Planas is a municipal barrio (district) of the town of Aibonito in Puerto Rico.
- 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c0bf5a48190bf245dceee24b579 |
completed | April 10, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eaf6c9ec8190bc0097d62e57e52a |
completed | May 3, 2026, 6:28 a.m. |
| NEDg | Description generation | batch_69f6ee07aa988190ad8bb3bc3ecf7890 |
completed | May 3, 2026, 6:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6eef335b481908dbe6fb93c9d56f2 |
completed | May 3, 2026, 6:45 a.m. |
Created at: April 9, 2026, 9:13 p.m.