Triple
T4575163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plane 0 |
E123125
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | BMP |
E123124
|
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: BMP | Statement: [Plane 0, alsoKnownAs, BMP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BMP Context triple: [Plane 0, alsoKnownAs, BMP]
-
A.
BMP
chosen
BMP is the Basic Multilingual Plane of Unicode, the primary block of code points that encodes the most commonly used characters from modern and many historic writing systems.
-
B.
DIB
DIB is the IATA airport code for Dibrugarh Airport, which serves the city of Dibrugarh in the Indian state of Assam.
-
C.
Tiff
Tiff is a common shortened form of the given name Tiffany, often used as a casual or affectionate nickname.
-
D.
BIP
BIP was the abbreviation for the Bureau of Information and Propaganda, a key Polish underground organization responsible for information, education, and psychological operations during World War II.
-
E.
BIF
BIF is the National Rail station code for Barrow-in-Furness railway station in Cumbria, England.
- 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_69bd46466c7081909d07f36be2d08804 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd58c9f0bc81908d87f01ab067818a |
completed | March 20, 2026, 2:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdd3e656a08190bb48d2ecae1eb798 |
completed | March 20, 2026, 11:10 p.m. |
Created at: March 20, 2026, 1:10 p.m.