Triple
T4749888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gimpo International Airport |
E105451
|
entity |
| Predicate | connectedBy |
P37
|
FINISHED |
| Object |
AREX
AREX is a South Korean airport railroad line that provides rapid rail transit between central Seoul and its major airports, including Gimpo and Incheon.
|
E467931
|
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: AREX | Statement: [Gimpo International Airport, connectedBy, AREX]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AREX Context triple: [Gimpo International Airport, connectedBy, AREX]
-
A.
REX
REX is a radio science experiment instrument aboard NASA's New Horizons spacecraft used to study the atmospheres and surfaces of planetary bodies through radio signal measurements.
-
B.
AKX
AKX is the IATA airport code for Aktobe International Airport in Aktobe, Kazakhstan.
-
C.
ARCX
ARCX is the Market Identifier Code for the NYSE Arca exchange, an electronic securities trading platform operated by the New York Stock Exchange.
-
D.
Arcop
Arcop was a prominent Canadian architectural firm known for its modernist designs and major cultural and institutional projects across Canada.
-
E.
AXS
AXS is a digital ticketing and event management platform known for selling and distributing tickets for sports, concerts, and live entertainment events.
- 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: AREX Triple: [Gimpo International Airport, connectedBy, AREX]
Generated description
AREX is a South Korean airport railroad line that provides rapid rail transit between central Seoul and its major airports, including Gimpo and Incheon.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AREX Target entity description: AREX is a South Korean airport railroad line that provides rapid rail transit between central Seoul and its major airports, including Gimpo and Incheon.
-
A.
REX
REX is a radio science experiment instrument aboard NASA's New Horizons spacecraft used to study the atmospheres and surfaces of planetary bodies through radio signal measurements.
-
B.
AKX
AKX is the IATA airport code for Aktobe International Airport in Aktobe, Kazakhstan.
-
C.
ARCX
ARCX is the Market Identifier Code for the NYSE Arca exchange, an electronic securities trading platform operated by the New York Stock Exchange.
-
D.
Arcop
Arcop was a prominent Canadian architectural firm known for its modernist designs and major cultural and institutional projects across Canada.
-
E.
AXS
AXS is a digital ticketing and event management platform known for selling and distributing tickets for sports, concerts, and live entertainment events.
- 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_69bd43f07fa48190954317d01600994a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64c83af48190bd57be79c1505e9d |
completed | March 20, 2026, 3:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be3a4e0844819098bb9abb05094a89 |
completed | March 21, 2026, 6:27 a.m. |
| NEDg | Description generation | batch_69be3c9f8e048190a951b26c36cb7b23 |
completed | March 21, 2026, 6:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be3d232b888190a0fd64c55a18eb48 |
completed | March 21, 2026, 6:39 a.m. |
Created at: March 20, 2026, 1:20 p.m.