Triple
T1630742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milan Linate Airport |
E35249
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object |
Segrate
Segrate is a municipality in the Metropolitan City of Milan in northern Italy, known for its proximity to Milan and its role as a residential and commercial suburb.
|
E278710
|
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: Segrate | Statement: [Milan Linate Airport, near, Segrate]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Segrate Context triple: [Milan Linate Airport, near, Segrate]
-
A.
Grignano
Grignano is a coastal locality near Trieste in northeastern Italy, known for its scenic bay and proximity to Miramare Castle.
-
B.
San Savino
San Savino is a small locality within the municipality of Predappio in the Emilia-Romagna region of northern Italy.
-
C.
Tremezzo
Tremezzo is a picturesque lakeside town in northern Italy’s Lombardy region, renowned for its historic villas, gardens, and scenic views over Lake Como.
-
D.
Cantù
Cantù is a town in the Lombardy region of northern Italy, known for its furniture-making tradition and location near Como.
-
E.
Imperia
Imperia is a coastal city in northwestern Italy’s Liguria region, known for its olive oil production, historic port, and seaside tourism.
- 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: Segrate Triple: [Milan Linate Airport, near, Segrate]
Generated description
Segrate is a municipality in the Metropolitan City of Milan in northern Italy, known for its proximity to Milan and its role as a residential and commercial suburb.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Segrate Target entity description: Segrate is a municipality in the Metropolitan City of Milan in northern Italy, known for its proximity to Milan and its role as a residential and commercial suburb.
-
A.
Grignano
Grignano is a coastal locality near Trieste in northeastern Italy, known for its scenic bay and proximity to Miramare Castle.
-
B.
San Savino
San Savino is a small locality within the municipality of Predappio in the Emilia-Romagna region of northern Italy.
-
C.
Tremezzo
Tremezzo is a picturesque lakeside town in northern Italy’s Lombardy region, renowned for its historic villas, gardens, and scenic views over Lake Como.
-
D.
Cantù
Cantù is a town in the Lombardy region of northern Italy, known for its furniture-making tradition and location near Como.
-
E.
Imperia
Imperia is a coastal city in northwestern Italy’s Liguria region, known for its olive oil production, historic port, and seaside tourism.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a909f5ae98819091ce5e00eb4256a2 |
completed | March 5, 2026, 4:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af6529905081909bd9e7c51fc21f77 |
completed | March 10, 2026, 12:26 a.m. |
| NEDg | Description generation | batch_69af66195b2c81908f9af299fe4966d4 |
completed | March 10, 2026, 12:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69af66a5c9c08190808ad50b1c9e258f |
completed | March 10, 2026, 12:32 a.m. |
Created at: March 4, 2026, 7:28 p.m.