Triple
T2239561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A train |
E49361
|
entity |
| Predicate | symbolLetter |
P5539
|
FINISHED |
| Object | A |
—
|
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: A | Statement: [A train, symbolLetter, A]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolLetter Context triple: [A train, symbolLetter, A]
-
A.
symbolType
Indicates the classification or category of a symbol based on its role, form, or function within a given system.
-
B.
alphabet
Indicates that one entity is an alphabet or set of symbols used for representing elements (such as characters or tokens) in relation to another entity.
-
C.
typicalSymbol
Indicates that something serves as a characteristic or commonly recognized symbol representing something else.
-
D.
letterSequence
Indicates that one sequence of letters directly follows or is ordered in relation to another within a larger string or alphabetic arrangement.
-
E.
hasLetterDesignation
chosen
Indicates that an entity is assigned or associated with a specific letter-based designation or code.
- 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_69a88aa84bdc819086df50e9c20b301e |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0bb3fac81908b1e8518951dd160 |
completed | March 7, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_69abbdafc07881909101266a33ae7031 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.