Triple
T180786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manchester Airport |
E3870
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object | MAN |
E3870
|
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: MAN | Statement: [Manchester Airport, IATAcode, MAN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MAN Context triple: [Manchester Airport, IATAcode, MAN]
-
A.
MAN
chosen
MAN is the three-letter IATA airport code for Manchester Airport, a major international airport serving the Greater Manchester area in England.
-
B.
Miller
Miller is a common English and Scottish occupational surname historically given to people who worked in grain mills.
-
C.
Mark
Mark is the given name of Mark Zuckerberg, the American technology entrepreneur and co-founder of Facebook.
-
D.
Levi
Levi is the surname of Primo Levi, the renowned Italian Jewish chemist and writer best known for his memoirs about surviving the Auschwitz concentration camp.
-
E.
Sen
Sen is a common Indian surname, particularly prevalent among Bengali communities and associated with numerous notable figures in academia, arts, and public life.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25901a9188190b8f510bec8c8e7f2 |
completed | Feb. 28, 2026, 2:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2f0b71080819086362f6036b41162 |
completed | Feb. 28, 2026, 1:42 p.m. |
Created at: Feb. 28, 2026, 2:40 a.m.