Triple
T7138350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr Goon |
E166369
|
entity |
| Predicate | typicalConflict |
P75056
|
FINISHED |
| Object | tries to solve mysteries before the children |
—
|
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: tries to solve mysteries before the children | Statement: [Mr Goon, typicalConflict, tries to solve mysteries before the children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalConflict Context triple: [Mr Goon, typicalConflict, tries to solve mysteries before the children]
-
A.
conflictIn
Indicates that one entity is involved in, associated with, or occurs within a particular conflict or dispute.
-
B.
mainConflict
Indicates the primary opposing force, problem, or struggle that drives tension and narrative progression between entities or sides.
-
C.
conflictSpecific
Indicates a specific, concrete instance or type of conflict that exists between the related entities.
-
D.
conflictType
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
E.
facesConflictWith
Indicates that one entity is in opposition, dispute, or contention with another, involving incompatible goals, interests, or actions.
- 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_69c68884a9388190af42f90d1c1a7151 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e694cc3c81908b0d54c2496a0722 |
completed | March 27, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c932888190b125ca3785b18553 |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e4a213508190a40aca39f9eee7d5 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:45 p.m.