Triple
T8631512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rue Morgue |
E204413
|
entity |
| Predicate | hasMotiveContext |
P84537
|
FINISHED |
| Object | apparently motiveless crime |
—
|
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: apparently motiveless crime | Statement: [Rue Morgue, hasMotiveContext, apparently motiveless crime]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMotiveContext Context triple: [Rue Morgue, hasMotiveContext, apparently motiveless crime]
-
A.
hasMotiveElement
Indicates that one entity includes, specifies, or is characterized by a particular motive-related component or factor in a broader relationship or action.
-
B.
hasMottoContext
Indicates that an entity’s motto is associated with or applies within a specific contextual setting or scope.
-
C.
hasMotiveTheme
Indicates that an action, event, or situation is associated with a central motivating theme or underlying driving idea.
-
D.
hasMotiveOfCriminals
Indicates that the specified motive is attributed to or associated with the criminals in question.
-
E.
hasMottoLanguageContext
Indicates that a motto is associated with a specific language context in which it is expressed or interpreted.
- 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_69ca834b903c8190add96cc651e1a477 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5730309081909a9a0256c9bf5f8f |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc455906f8819082edd79cb4a1cf28 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc572d99bc819097f36b140c2ee1ce |
completed | March 31, 2026, 11:22 p.m. |
Created at: March 30, 2026, 6:27 p.m.