Triple
T32125651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howard Silk |
E820493
|
entity |
| Predicate | counterpartPersonalityTrait |
P37384
|
FINISHED |
| Object | ruthless |
—
|
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: ruthless | Statement: [Howard Silk, counterpartPersonalityTrait, ruthless]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: counterpartPersonalityTrait Context triple: [Howard Silk, counterpartPersonalityTrait, ruthless]
-
A.
associatedCharacterTrait
chosen
Indicates a relationship where a character is linked to, or described by, a particular trait or quality.
-
B.
secondaryCharacterTrait
Indicates that a secondary or supporting character possesses a particular attribute, quality, or personality trait.
-
C.
emotionalCounterpartOf
Indicates that one entity serves as the emotional equivalent, complement, or matching emotional role of another entity.
-
D.
counterpartTerm
Indicates that one term serves as a corresponding or equivalent term to another within a specific relational or comparative context.
-
E.
counterpartRelation
Indicates a reciprocal relationship where two entities serve as corresponding or equivalent counterparts to each other in a given context.
- 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_69f34902d42c819083a8e6bba9a8bb9a |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a00315632a8819092290f455babd7ee |
completed | May 10, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_6a002f54a0dc81909b0e54c5e110e67c |
completed | May 10, 2026, 7:10 a.m. |
Created at: May 1, 2026, 12:29 a.m.