Triple
T2265822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Springfield–Beckley Municipal Airport |
E50142
|
entity |
| Predicate | IATACode |
P418
|
FINISHED |
| Object |
SGH
SGH is the IATA airport code for Springfield–Beckley Municipal Airport in Springfield, Ohio, United States.
|
E251580
|
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: SGH | Statement: [Springfield–Beckley Municipal Airport, IATACode, SGH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SGH Context triple: [Springfield–Beckley Municipal Airport, IATACode, SGH]
-
A.
SGN
SGN is the IATA airport code for Tan Son Nhat International Airport, the main international gateway serving Ho Chi Minh City, Vietnam.
-
B.
S8
S8 is a line of the Berlin S-Bahn urban rail network serving various districts across the Berlin metropolitan area.
-
C.
HK G3 series
The HK G3 series is a family of 7.62×51mm NATO battle rifles developed in the 1950s that became one of the most widely used and influential military rifles worldwide.
-
D.
KGH
KGH is the National Rail station code for Kinghorn railway station in Fife, Scotland.
-
E.
Sudogwon
Sudogwon is the Seoul Capital Area of South Korea, encompassing Seoul, Incheon, and surrounding Gyeonggi Province as the country’s largest and most populous metropolitan 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: SGH Triple: [Springfield–Beckley Municipal Airport, IATACode, SGH]
Generated description
SGH is the IATA airport code for Springfield–Beckley Municipal Airport in Springfield, Ohio, United States.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SGH Target entity description: SGH is the IATA airport code for Springfield–Beckley Municipal Airport in Springfield, Ohio, United States.
-
A.
SGN
SGN is the IATA airport code for Tan Son Nhat International Airport, the main international gateway serving Ho Chi Minh City, Vietnam.
-
B.
S8
S8 is a line of the Berlin S-Bahn urban rail network serving various districts across the Berlin metropolitan area.
-
C.
HK G3 series
The HK G3 series is a family of 7.62×51mm NATO battle rifles developed in the 1950s that became one of the most widely used and influential military rifles worldwide.
-
D.
KGH
KGH is the National Rail station code for Kinghorn railway station in Fife, Scotland.
-
E.
Sudogwon
Sudogwon is the Seoul Capital Area of South Korea, encompassing Seoul, Incheon, and surrounding Gyeonggi Province as the country’s largest and most populous metropolitan 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc18fff0c8190acd73d8db8a41cff |
completed | March 7, 2026, 6:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71d243608190bbfe5784fa06e26b |
completed | March 9, 2026, 7:08 a.m. |
| NEDg | Description generation | batch_69ae728e46608190b4192519c705bc32 |
completed | March 9, 2026, 7:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae72ff572081909b7c4aebb9e26180 |
completed | March 9, 2026, 7:13 a.m. |
Created at: March 4, 2026, 7:48 p.m.