Triple
T3774930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaffna Public Library |
E83284
|
entity |
| Predicate | hasReferenceSection |
P43838
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Jaffna Public Library, hasReferenceSection, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReferenceSection Context triple: [Jaffna Public Library, hasReferenceSection, yes]
-
A.
hasSect
Indicates that an entity includes, contains, or is associated with a particular sect or subgroup within a larger religious, ideological, or organizational context.
-
B.
hasSectionOn
chosen
Indicates that one entity (typically a document or resource) contains a dedicated section or part that specifically addresses or discusses another entity or topic.
-
C.
hasSectionIn
Indicates that one entity contains or includes another entity as a section or subdivision within it.
-
D.
hasReferenceWork
Indicates that one entity is associated with a reference work (such as a dictionary, encyclopedia, or manual) that provides authoritative information about it.
-
E.
hasInfluentialSection
Indicates that one part or section of something has a significant impact on, or strongly shapes, another entity or the overall outcome.
- 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_69ad8b235e608190b5a2b1d1bfcef50b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc5ac9688190bc921cd3ba1d0580 |
completed | March 8, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_69adc050cc5c81909d9855f866f3c26d |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:36 p.m.