Triple
T32590973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walauwa |
E833062
|
entity |
| Predicate | relatedLanguageTerm |
P87230
|
FINISHED |
| Object | Sinhala architecture terminology |
—
|
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: Sinhala architecture terminology | Statement: [Walauwa, relatedLanguageTerm, Sinhala architecture terminology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedLanguageTerm Context triple: [Walauwa, relatedLanguageTerm, Sinhala architecture terminology]
-
A.
linguisticallyRelatedTo
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
-
B.
linkedToLanguage
chosen
Indicates that an entity has an association or connection with a specific language, such as being expressed in, related to, or dependent on that language.
-
C.
closelyAssociatedLanguage
Indicates that one language is closely connected to another, such as through frequent co-use, mutual influence, or strong cultural or regional association.
-
D.
termLanguage
Indicates the language in which a given term is expressed or defined.
-
E.
hasRelatedLanguage
Indicates that one language is related to another through shared linguistic origins, features, or classification.
- 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_69f34929ff648190aded9424aa7564ae |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:05 a.m.