Triple
T10413163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Arab Airlines |
E245445
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object | MSR |
E245444
|
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: MSR | Statement: [United Arab Airlines, ICAOcode, MSR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MSR Context triple: [United Arab Airlines, ICAOcode, MSR]
-
A.
MSR
chosen
MSR is the ICAO airline designator used to identify EgyptAir in international aviation operations.
-
B.
MSR Cambridge
MSR Cambridge is a leading Microsoft Research lab based in Cambridge, UK, known for pioneering work in areas such as machine learning, artificial intelligence, and human-computer interaction.
-
C.
MRS
MRS is the Materials Research Society, a professional organization dedicated to advancing interdisciplinary materials science and engineering research and education.
-
D.
MSA
MSA is the standardized, literary form of Arabic used in formal writing, media, education, and official communication across the Arab world.
-
E.
MSA
MSA is a common abbreviation for a metropolitan statistical area, a region defined by the U.S. Office of Management and Budget for statistical and demographic analysis.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea0e17f081908fb16425f65e5808 |
completed | April 7, 2026, 11:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fc043074819083d219ec1c40f931 |
completed | April 9, 2026, 7:20 p.m. |
Created at: April 6, 2026, 12:10 p.m.