Triple
T15111488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giuseppe Terragni |
E360921
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Meda, Italy
Meda, Italy is a town in the Lombardy region of northern Italy, known for its furniture-making tradition and proximity to Milan.
|
E1138934
|
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: Meda, Italy | Statement: [Giuseppe Terragni, placeOfBirth, Meda, Italy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meda, Italy Context triple: [Giuseppe Terragni, placeOfBirth, Meda, Italy]
-
A.
Montella, Italy
Montella, Italy is a small town in the Campania region of southern Italy, known for its mountainous landscape and traditional chestnut production.
-
B.
Tivoli, Italy
Tivoli, Italy is a historic town near Rome renowned for its ancient villas, spectacular gardens, and scenic waterfalls.
-
C.
Ome, Italy
Ome is a small municipality in the Lombardy region of northern Italy, known for its wine production and scenic location in the hills near Brescia.
-
D.
Arese, Italy
Arese, Italy is a town in the Lombardy region best known for its historic Alfa Romeo automobile manufacturing plant and automotive heritage.
-
E.
Cairano, Italy
Cairano, Italy is a small hilltop village in the Campania region of southern Italy, known for its scenic landscapes and traditional rural character.
- 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: Meda, Italy Triple: [Giuseppe Terragni, placeOfBirth, Meda, Italy]
Generated description
Meda, Italy is a town in the Lombardy region of northern Italy, known for its furniture-making tradition and proximity to Milan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Meda, Italy Target entity description: Meda, Italy is a town in the Lombardy region of northern Italy, known for its furniture-making tradition and proximity to Milan.
-
A.
Montella, Italy
Montella, Italy is a small town in the Campania region of southern Italy, known for its mountainous landscape and traditional chestnut production.
-
B.
Tivoli, Italy
Tivoli, Italy is a historic town near Rome renowned for its ancient villas, spectacular gardens, and scenic waterfalls.
-
C.
Ome, Italy
Ome is a small municipality in the Lombardy region of northern Italy, known for its wine production and scenic location in the hills near Brescia.
-
D.
Arese, Italy
Arese, Italy is a town in the Lombardy region best known for its historic Alfa Romeo automobile manufacturing plant and automotive heritage.
-
E.
Cairano, Italy
Cairano, Italy is a small hilltop village in the Campania region of southern Italy, known for its scenic landscapes and traditional rural character.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0058d786c8190937c6819255c01bd |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7eb139c8190b76393e4a8be576b |
completed | May 9, 2026, 4:28 a.m. |
| NEDg | Description generation | batch_69feb9f7b6d88190886fd65ce736ed1b |
completed | May 9, 2026, 4:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69febaa20ffc819090dd4b113d8513d7 |
completed | May 9, 2026, 4:40 a.m. |
Created at: April 10, 2026, 3:05 a.m.