Triple
T15147042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SAGAT S.p.A. |
E361836
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
SAGAT
SAGAT is an Italian airport management company best known for operating Turin Airport.
|
E1140518
|
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: SAGAT | Statement: [SAGAT S.p.A., abbreviation, SAGAT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SAGAT Context triple: [SAGAT S.p.A., abbreviation, SAGAT]
-
A.
Sagal
Sagal is a surname most notably associated with a family of American actors and entertainers, including Jean Sagal and her relatives.
-
B.
Santok
Santok is a historic village in western Poland, long known as a strategic fortified settlement at the confluence of the Noteć and Warta rivers.
-
C.
Saihat
Saihat is a coastal city in Saudi Arabia’s Eastern Province, known for its fishing heritage and proximity to major oil and industrial centers in the Gulf region.
-
D.
Sagàs
Sagàs is a small rural municipality in the Berguedà comarca of Catalonia, Spain, known for its agricultural landscape and traditional Catalan countryside.
-
E.
Sakakah
Sakakah is a city in northwestern Saudi Arabia that serves as the administrative and economic center of the Al Jawf 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: SAGAT Triple: [SAGAT S.p.A., abbreviation, SAGAT]
Generated description
SAGAT is an Italian airport management company best known for operating Turin Airport.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SAGAT Target entity description: SAGAT is an Italian airport management company best known for operating Turin Airport.
-
A.
Sagal
Sagal is a surname most notably associated with a family of American actors and entertainers, including Jean Sagal and her relatives.
-
B.
Santok
Santok is a historic village in western Poland, long known as a strategic fortified settlement at the confluence of the Noteć and Warta rivers.
-
C.
Saihat
Saihat is a coastal city in Saudi Arabia’s Eastern Province, known for its fishing heritage and proximity to major oil and industrial centers in the Gulf region.
-
D.
Sagàs
Sagàs is a small rural municipality in the Berguedà comarca of Catalonia, Spain, known for its agricultural landscape and traditional Catalan countryside.
-
E.
Sakakah
Sakakah is a city in northwestern Saudi Arabia that serves as the administrative and economic center of the Al Jawf 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005c825a481909d00098b0e743365 |
completed | April 15, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69febff02e648190bd10f04a374da227 |
completed | May 9, 2026, 5:02 a.m. |
| NEDg | Description generation | batch_69fec08c37dc8190a59289e4ee76beab |
completed | May 9, 2026, 5:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fec10cd2d48190ba96885ca604a853 |
completed | May 9, 2026, 5:07 a.m. |
Created at: April 10, 2026, 3:07 a.m.