Triple
T2518965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinhala script |
E55476
|
entity |
| Predicate | hasDistinctSetFor |
P40750
|
FINISHED |
| Object | pure Sinhala consonants |
—
|
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: pure Sinhala consonants | Statement: [Sinhala script, hasDistinctSetFor, pure Sinhala consonants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDistinctSetFor Context triple: [Sinhala script, hasDistinctSetFor, pure Sinhala consonants]
-
A.
hasDistinctFeature
Indicates that an entity possesses a specific characteristic or attribute that differentiates it from others.
-
B.
hasDistinctIdentity
Indicates that an entity possesses its own unique, distinguishable identity separate from other entities.
-
C.
hasDistinctHead
Indicates that an entity possesses a head that is clearly separate or distinguishable from the rest of its body or structure.
-
D.
hasDistinctLetters
Indicates that all letters in the given string or word are unique, with no character repeated.
-
E.
hasDistinctLettersFor
Indicates that one entity is associated with another such that the letters used in the first are all different from (i.e., share no letters with) those used in the second.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69abd5a1cd508190a660b9a3c6b7cbcb |
completed | March 7, 2026, 7:37 a.m. |
Created at: March 6, 2026, 9:46 p.m.