Triple
T1629337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guangzhou Baiyun International Airport |
E35221
|
entity |
| Predicate | hasAirportCode |
P6089
|
FINISHED |
| Object | ZGGG |
E185254
|
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: ZGGG | Statement: [Guangzhou Baiyun International Airport, hasAirportCode, ZGGG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ZGGG Context triple: [Guangzhou Baiyun International Airport, hasAirportCode, ZGGG]
-
A.
ZGGG
chosen
ZGGG is the ICAO airport code for Guangzhou Baiyun International Airport, a major aviation hub serving Guangzhou in southern China.
-
B.
ZG
ZG is the vehicle registration code used on license plates for the city of Zagreb, the capital of Croatia.
-
C.
ZZ
ZZ is an aircraft registration prefix used to identify certain aircraft, such as those in the Voyager KC2 fleet.
-
D.
GG
GG was the original designation for New York City's G subway service, a crosstown line that runs through Brooklyn and Queens without entering Manhattan.
-
E.
BZZ
BZZ is the IATA airport code for RAF Brize Norton, a major Royal Air Force transport and air-to-air refuelling base in Oxfordshire, England.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a909f257948190b3398fd6dc91f586 |
completed | March 5, 2026, 4:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad6096584c81909ce50469f23a8a12 |
completed | March 8, 2026, 11:42 a.m. |
Created at: March 4, 2026, 7:28 p.m.