Triple
T217754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryanair |
E4144
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object |
FR
FR is the IATA airline designator used to identify Ryanair flights.
|
E27865
|
NE FINISHED |
How this triple was built (4 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: FR | Statement: [Ryanair, IATAcode, FR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FR Context triple: [Ryanair, IATAcode, FR]
-
A.
French
French is a Romance language that evolved from Latin and is now spoken worldwide as both a native and official language in many countries.
-
B.
France
France is a major Western European nation known for its influential history, culture, and economy, and as a founding member of the European Union and the United Nations.
-
C.
MFL
MFL is a common abbreviation for "Modern Foreign Languages," typically referring to the study of contemporary non-native languages in educational settings.
-
D.
Francophonie
Francophonie is the global community of French-speaking countries, regions, and peoples connected by the use of the French language and shared cultural and institutional ties.
-
E.
F
F is the New York Stock Exchange ticker symbol for Ford Motor Company, the American multinational automaker known for mass-producing automobiles and pioneering assembly line manufacturing.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: FR Triple: [Ryanair, IATAcode, FR]
Generated description
FR is the IATA airline designator used to identify Ryanair flights.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: FR Target entity description: FR is the IATA airline designator used to identify Ryanair flights.
-
A.
French
French is a Romance language that evolved from Latin and is now spoken worldwide as both a native and official language in many countries.
-
B.
France
France is a major Western European nation known for its influential history, culture, and economy, and as a founding member of the European Union and the United Nations.
-
C.
MFL
MFL is a common abbreviation for "Modern Foreign Languages," typically referring to the study of contemporary non-native languages in educational settings.
-
D.
Francophonie
Francophonie is the global community of French-speaking countries, regions, and peoples connected by the use of the French language and shared cultural and institutional ties.
-
E.
F
F is the New York Stock Exchange ticker symbol for Ford Motor Company, the American multinational automaker known for mass-producing automobiles and pioneering assembly line manufacturing.
- F. None of above. chosen
Provenance (5 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c5062e48190833be10e4770e1e9 |
completed | Feb. 28, 2026, 3:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3441e48b48190849c7bff04134ac9 |
completed | Feb. 28, 2026, 7:38 p.m. |
| NEDg | Description generation | batch_69a344ba0a4c8190986d490f502cb6ab |
completed | Feb. 28, 2026, 7:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a34520805481909c4f1ea05262665b |
completed | Feb. 28, 2026, 7:42 p.m. |
Created at: Feb. 28, 2026, 2:53 a.m.