Triple
T11039422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canton Municipal Airport |
E260968
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object |
City of Canton
The City of Canton is a local municipal government that administers public services and infrastructure, including the Canton Municipal Airport, for its community.
|
E900811
|
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: City of Canton | Statement: [Canton Municipal Airport, owner, City of Canton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Canton Context triple: [Canton Municipal Airport, owner, City of Canton]
-
A.
Loja Canton
Loja Canton is an administrative subdivision in southern Ecuador that encompasses the city of Loja and its surrounding areas.
-
B.
Ngã Tư Sở
Ngã Tư Sở is a major traffic junction and commercial hub in southwestern Hanoi, Vietnam, connecting several key urban districts.
-
C.
Changle
Changle is a coastal city in eastern China located on the Shandong Peninsula.
-
D.
Guandu
Guandu is a district in northern Taipei, Taiwan, known for its riverside wetlands, hot springs, and the historic Guandu Temple.
-
E.
Cathay City
Cathay City is Cathay Pacific’s purpose-built corporate headquarters complex located near Hong Kong International Airport, housing the airline’s main offices, training facilities, and support operations.
- 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: City of Canton Triple: [Canton Municipal Airport, owner, City of Canton]
Generated description
The City of Canton is a local municipal government that administers public services and infrastructure, including the Canton Municipal Airport, for its community.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: City of Canton Target entity description: The City of Canton is a local municipal government that administers public services and infrastructure, including the Canton Municipal Airport, for its community.
-
A.
Loja Canton
Loja Canton is an administrative subdivision in southern Ecuador that encompasses the city of Loja and its surrounding areas.
-
B.
Ngã Tư Sở
Ngã Tư Sở is a major traffic junction and commercial hub in southwestern Hanoi, Vietnam, connecting several key urban districts.
-
C.
Changle
Changle is a coastal city in eastern China located on the Shandong Peninsula.
-
D.
Guandu
Guandu is a district in northern Taipei, Taiwan, known for its riverside wetlands, hot springs, and the historic Guandu Temple.
-
E.
Cathay City
Cathay City is Cathay Pacific’s purpose-built corporate headquarters complex located near Hong Kong International Airport, housing the airline’s main offices, training facilities, and support operations.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797ff519481909ebc2515b3d241de |
completed | April 9, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3a9d61b548190949f0dfbcb782064 |
completed | April 18, 2026, 3:57 p.m. |
| NEDg | Description generation | batch_69e3ad00b5c08190a7bf3ecbeae76d88 |
completed | April 18, 2026, 4:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3b1fff754819092d634f46fb42387 |
completed | April 18, 2026, 4:32 p.m. |
Created at: April 8, 2026, 9:26 p.m.