Triple
T11942383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 3 (São Paulo–Guarulhos International Airport) |
E284207
|
entity |
| Predicate | IATAAirportCodeOfParent |
P2569
|
FINISHED |
| Object | GRU |
E284205
|
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: GRU | Statement: [Terminal 3 (São Paulo–Guarulhos International Airport), IATAAirportCodeOfParent, GRU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GRU Context triple: [Terminal 3 (São Paulo–Guarulhos International Airport), IATAAirportCodeOfParent, GRU]
-
A.
GRU
GRU is Russia’s military intelligence agency, known for conducting espionage, cyber operations, and covert activities abroad.
-
B.
GRU
chosen
GRU is the IATA airport code for São Paulo–Guarulhos International Airport, the main international gateway serving São Paulo, Brazil.
-
C.
RBM
RBM is a global partnership initiative dedicated to coordinating and scaling up efforts to prevent, control, and ultimately eliminate malaria worldwide.
-
D.
SGD
SGD is the official currency code for the Singapore dollar, the national currency of Singapore used in domestic and international transactions.
-
E.
SGD
SGD is the commonly used abbreviation and nickname for the German football club Dynamo Dresden.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90342bb908190a019ac91a2b82f3d |
completed | April 10, 2026, 2:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f458b9a35c8190875cb5ac7c9bcfba |
completed | May 1, 2026, 7:39 a.m. |
Created at: April 8, 2026, 9:45 p.m.