Triple
T525284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CDG |
E10902
|
entity |
| Predicate | hasSubTerminal |
P15145
|
FINISHED |
| Object | Terminal 2G |
E65653
|
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: Terminal 2G | Statement: [CDG, hasSubTerminal, Terminal 2G]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terminal 2G Context triple: [CDG, hasSubTerminal, Terminal 2G]
-
A.
Terminal 2D
chosen
Terminal 2D is a passenger terminal at Paris Charles de Gaulle Airport, serving as one of the facilities handling flights and travelers at this major international hub.
-
B.
Terminal 2
Terminal 2 is a modern, sustainably designed passenger terminal at San Francisco International Airport known for its upgraded amenities, art installations, and improved traveler experience.
-
C.
Terminal 2
Terminal 2 is a major passenger terminal at Wuhan Tianhe International Airport, serving as one of the airport’s primary facilities for domestic and international air travel operations.
-
D.
Terminal 2
Terminal 2 is a major passenger terminal at Ronald Reagan Washington National Airport serving numerous domestic airline operations and traveler amenities.
-
E.
Terminal 2
Terminal 2 is the newer, modern passenger terminal at Mexico City International Airport, serving as a major hub for several domestic and international airlines.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f3b7557c8190a29cf1de359ea2ea |
completed | Feb. 28, 2026, 1:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4b5d71fa881908c52d2a675b5b7d1 |
completed | March 1, 2026, 9:55 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.