Triple
T2502707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wuhan Tianhe International Airport |
E52500
|
entity |
| Predicate | hasIATACode |
P2569
|
FINISHED |
| Object | WUH |
E52500
|
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: WUH | Statement: [Wuhan Tianhe International Airport, hasIATACode, WUH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WUH Context triple: [Wuhan Tianhe International Airport, hasIATACode, WUH]
-
A.
WUH
chosen
WUH is the IATA airport code for Wuhan Tianhe International Airport, the main air gateway serving Wuhan in central China.
-
B.
WU
WU is the stock ticker symbol for Western Union, a global financial services company best known for its money transfer and payment services.
-
C.
WU
WU is a leading European university in Vienna specializing in economics, business, and social sciences.
-
D.
WÜ
WÜ is the vehicle registration code for the city and district of Würzburg in the Lower Franconia region of Bavaria, Germany.
-
E.
WUN
WUN is the vehicle registration code for the district of Wunsiedel im Fichtelgebirge in Upper Franconia, Germany.
- 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_69ab4957b3a88190adf968ae0c1b931c |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1cb4f6481908d4e0a1dc0d84d3c |
completed | March 7, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af2b8bc7708190a507136d1f9f34ca |
completed | March 9, 2026, 8:20 p.m. |
Created at: March 6, 2026, 9:46 p.m.