Triple
T14743921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Y class |
E346417
|
entity |
| Predicate | codedUsing |
P1444
|
FINISHED |
| Object | single-letter booking code |
—
|
LITERAL 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: single-letter booking code | Statement: [Y class, codedUsing, single-letter booking code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codedUsing Context triple: [Y class, codedUsing, single-letter booking code]
-
A.
encodedIn
chosen
Indicates that one entity is represented, stored, or expressed within another entity using a specific encoding or format.
-
B.
encodes
Indicates that one entity contains or represents the information, instructions, or structure of another in a coded or symbolic form.
-
C.
codingUnit
Indicates a relationship where an entity functions as or is associated with a specific unit of code or coding structure.
-
D.
usesCodec
Indicates that one entity employs or relies on a specific codec to encode, decode, or process data.
-
E.
codeword
Indicates that one entity serves as a codeword or encoded representation used to convey, reference, or stand in for another entity within a coding or communication system.
- F. None of above.
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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7367a1c819081082cc355e385fa |
completed | April 14, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69de8bf9331481909582045cd567d91f |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:30 a.m.