Triple
T11039423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canton Municipal Airport |
E260968
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | City of Canton |
E900811
|
NE FINISHED |
How this triple was built (2 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, operator, 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, operator, City of Canton]
-
A.
City of Canton
chosen
The City of Canton is a local municipal government that administers public services and infrastructure, including the Canton Municipal Airport, for its community.
-
B.
Loja Canton
Loja Canton is an administrative subdivision in southern Ecuador that encompasses the city of Loja and its surrounding areas.
-
C.
Ngã Tư Sở
Ngã Tư Sở is a major traffic junction and commercial hub in southwestern Hanoi, Vietnam, connecting several key urban districts.
-
D.
Changle
Changle is a coastal city in eastern China located on the Shandong Peninsula.
-
E.
Guandu
Guandu is a district in northern Taipei, Taiwan, known for its riverside wetlands, hot springs, and the historic Guandu Temple.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69e3c846d9f08190943d457ff6da6a9f |
completed | April 18, 2026, 6:07 p.m. |
Created at: April 8, 2026, 9:26 p.m.