Triple
T8508104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | InformRequest-PDU |
E201384
|
entity |
| Predicate | hasSemantic |
P28757
|
FINISHED |
| Object | inform notification |
—
|
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: inform notification | Statement: [InformRequest-PDU, hasSemantic, inform notification]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSemantic Context triple: [InformRequest-PDU, hasSemantic, inform notification]
-
A.
hasSemantics
chosen
Indicates that one entity carries or encodes the meaning, interpretation, or semantic content associated with another entity.
-
B.
hasSemanticsDefinedBy
Indicates that the meaning or interpretation of one entity is specified, constrained, or determined by another entity.
-
C.
hasSemanticRestriction
Indicates that a concept or relation is constrained in meaning or usage by specific semantic conditions or limitations.
-
D.
hasLiteralMeaning
Indicates that one entity expresses the direct, explicit meaning or sense of another entity (such as a word, phrase, or symbol).
-
E.
hasSense
Indicates that an entity possesses or is associated with a particular sensory perception, meaning, or interpretation.
- 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_69ca8320e5748190ac2c585a0bba8193 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe5df74e8819086b1445cc907e371 |
completed | March 31, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69cbd10cfd208190a519049fad32c508 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:15 p.m.