Triple
T5534128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | January |
E145117
|
entity |
| Predicate | hasTypicalSymbol |
P18980
|
FINISHED |
| Object | garnet (birthstone association) |
—
|
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: garnet (birthstone association) | Statement: [January, hasTypicalSymbol, garnet (birthstone association)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalSymbol Context triple: [January, hasTypicalSymbol, garnet (birthstone association)]
-
A.
typicalSymbol
chosen
Indicates that something serves as a characteristic or commonly recognized symbol representing something else.
-
B.
hasTypicalCharacterType
Indicates that an entity is commonly associated with or exemplified by a particular type of character or persona.
-
C.
hasTraditionalSymbol
Indicates that something is associated with or represented by a conventional or culturally established symbol.
-
D.
hasTypicalSubject
Indicates that something is commonly or characteristically used as the subject (agent or topic) of a given relation or action.
-
E.
symbolType
Indicates the classification or category of a symbol based on its role, form, or function within a given 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_69c008f9955881909bfa8348b56b4739 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fa0141c81909a216be9f48d64e1 |
completed | March 22, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69c01b0c50e48190a1b03ecd20ca440b |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:34 p.m.