Triple
T16927171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 1 |
E410604
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Terminal 1 |
unclear NED1
|
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 1 | Statement: [Terminal 1, name, Terminal 1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terminal 1 Context triple: [Terminal 1, name, Terminal 1]
-
A.
Terminal 1
Terminal 1 is one of the main passenger terminals at Paris Charles de Gaulle Airport, known for its distinctive circular design and central location within the airport complex.
-
B.
Terminal 1
Terminal 1 is the main passenger terminal at El Dorado International Airport in Bogotá, Colombia, handling the majority of the airport’s domestic and international flights.
-
C.
Terminal 1
Terminal 1 is the main passenger terminal at Brussels South Charleroi Airport, handling the majority of the airport’s commercial flights and traveler services.
-
D.
Terminal 1
Terminal 1 is the main passenger terminal at Milan Malpensa Airport, handling the bulk of its international and domestic flights with extensive services and facilities.
-
E.
Terminal 1
Terminal 1 is a domestic passenger terminal at Sardar Vallabhbhai Patel International Airport in Ahmedabad, India.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d886c7b1e481908c3766dfa8c13458 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cdf2dcd881909798bd245e18c599 |
completed | April 18, 2026, 6:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d45c32a08190970137790d08f499 |
completed | May 10, 2026, 6:54 p.m. |
Created at: April 10, 2026, 5:30 a.m.