Triple
T400789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Modula-3 |
E9274
|
entity |
| Predicate | hasExceptionConstruct |
P12990
|
FINISHED |
| Object | RAISE |
—
|
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: RAISE | Statement: [Modula-3, hasExceptionConstruct, RAISE]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExceptionConstruct Context triple: [Modula-3, hasExceptionConstruct, RAISE]
-
A.
hasCause
Indicates that one entity is the reason for, or brings about, the occurrence or existence of another entity or event.
-
B.
hasCase
Indicates that one entity is involved in, associated with, or characterized by a particular case, instance, or occurrence represented by another entity.
-
C.
throws
Indicates that one entity propels or hurls another entity or object through space, typically by a deliberate physical action.
-
D.
hasCondition
Indicates that an entity possesses, experiences, or is affected by a particular condition or state.
-
E.
hasDefinition
Indicates that one entity provides the meaning, explanation, or definition of another entity.
- 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ec8e655c819081eff85c0ef55fa5 |
completed | Feb. 28, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69a2e96ee4ec8190a5c0e3f491d3963d |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2eb7c56bc8190ab787801af2eec8d |
completed | Feb. 28, 2026, 1:19 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.