Triple
T4199461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Léopold Sédar Senghor International Airport |
E86030
|
entity |
| Predicate | hasCode |
P9567
|
FINISHED |
| Object | DKR |
E420453
|
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: DKR | Statement: [Léopold Sédar Senghor International Airport, hasCode, DKR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DKR Context triple: [Léopold Sédar Senghor International Airport, hasCode, DKR]
-
A.
DKR
chosen
DKR is the IATA airport code for Léopold Sédar Senghor International Airport, the former main international gateway to Dakar, Senegal.
-
B.
DK
DK is a British illustrated reference publisher best known for its highly visual nonfiction books for children and adults across topics like science, history, travel, and nature.
-
C.
DK
DK is the ISO 3166-1 alpha-2 country code for Denmark, a Nordic nation in Northern Europe.
-
D.
DK
DK is the standard scholarly abbreviation for the Diels–Kranz collection of pre-Socratic Greek philosophical fragments.
-
E.
RKR
RKR is the vehicle registration code assigned to vehicles registered in the Rymanów area of Poland.
- 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_69aed93b89f48190a31f6d57c760e42f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af036243b4819097efe6b796823cd9 |
completed | March 9, 2026, 5:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5962296b8819084b91de3f48b7658 |
completed | March 14, 2026, 5:08 p.m. |
Created at: March 9, 2026, 3:49 p.m.