Triple
T15015263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No. 3 Flying Training School RAF |
E377942
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
3 FTS
3 FTS is a Royal Air Force flying training unit responsible for instructing and qualifying new military pilots in the United Kingdom.
|
E1132524
|
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: 3 FTS | Statement: [No. 3 Flying Training School RAF, hasAbbreviation, 3 FTS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 3 FTS Context triple: [No. 3 Flying Training School RAF, hasAbbreviation, 3 FTS]
-
A.
FTS
FTS is the commonly used abbreviation for the Financial Tracking Service, a global humanitarian aid financial tracking system managed by the United Nations.
-
B.
F-3
F-3 is a three-quarter-ton model in Ford’s first-generation postwar F-Series pickup truck lineup, known as the “Bonus-Built” trucks produced in the late 1940s and early 1950s.
-
C.
FSR 3
FSR 3 is AMD’s third-generation FidelityFX Super Resolution technology that enhances gaming performance and visual quality through advanced upscaling and frame generation.
-
D.
F32
F32 is BMW’s internal model code for the first-generation 4 Series coupe, introduced as a sporty, premium compact executive car.
-
E.
F33
F33 is BMW’s internal designation for the first-generation 4 Series convertible model.
- 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: 3 FTS Triple: [No. 3 Flying Training School RAF, hasAbbreviation, 3 FTS]
Generated description
3 FTS is a Royal Air Force flying training unit responsible for instructing and qualifying new military pilots in the United Kingdom.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 3 FTS Target entity description: 3 FTS is a Royal Air Force flying training unit responsible for instructing and qualifying new military pilots in the United Kingdom.
-
A.
FTS
FTS is the commonly used abbreviation for the Financial Tracking Service, a global humanitarian aid financial tracking system managed by the United Nations.
-
B.
F-3
F-3 is a three-quarter-ton model in Ford’s first-generation postwar F-Series pickup truck lineup, known as the “Bonus-Built” trucks produced in the late 1940s and early 1950s.
-
C.
FSR 3
FSR 3 is AMD’s third-generation FidelityFX Super Resolution technology that enhances gaming performance and visual quality through advanced upscaling and frame generation.
-
D.
F32
F32 is BMW’s internal model code for the first-generation 4 Series coupe, introduced as a sporty, premium compact executive car.
-
E.
F33
F33 is BMW’s internal designation for the first-generation 4 Series convertible model.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7623c3c819092ca36b358b01842 |
completed | April 15, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe96aa3c888190a65e7b3c3b130131 |
completed | May 9, 2026, 2:06 a.m. |
| NEDg | Description generation | batch_69fe97af0a0c8190bca3ea103d05fd99 |
completed | May 9, 2026, 2:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe98b18ab48190b2a47418904e6643 |
completed | May 9, 2026, 2:15 a.m. |
Created at: April 10, 2026, 2:55 a.m.