Triple
T2518962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinhala script |
E55476
|
entity |
| Predicate | hasHistoricalVariant |
P455
|
FINISHED |
| Object | medieval Sinhala script |
—
|
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: medieval Sinhala script | Statement: [Sinhala script, hasHistoricalVariant, medieval Sinhala script]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalVariant Context triple: [Sinhala script, hasHistoricalVariant, medieval Sinhala script]
-
A.
hasHistoricalEntity
Indicates a relationship where one entity includes, references, or is associated with another entity that existed or is defined in a past historical context.
-
B.
hasHistoricalPrecursor
Indicates that one entity existed earlier and served as a predecessor, model, or influential forerunner to the other in a historical context.
-
C.
hasVariant
chosen
Indicates that one entity exists as an alternative form, version, or variation of another entity.
-
D.
hasTypeHistory
Indicates that an entity is associated with a record or sequence of its past and present types or classifications over time.
-
E.
hasHistoricalShiftTo
Indicates a change over time in which one state, condition, or configuration is replaced or transformed into another in a historically traceable way.
- 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_69ab49e4749c8190813311efd1630f1b |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd5a33234819082ad49fa6594b6be |
completed | March 7, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69abd0bf37c0819088d28b5081ba7556 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.