Triple
T16457151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Doe (Se7en) |
E399711
|
entity |
| Predicate | killsByMethod |
P122855
|
FINISHED |
| Object | murders modeled on seven deadly sins |
—
|
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: murders modeled on seven deadly sins | Statement: [John Doe (Se7en), killsByMethod, murders modeled on seven deadly sins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: killsByMethod Context triple: [John Doe (Se7en), killsByMethod, murders modeled on seven deadly sins]
-
A.
killsByProxy
Indicates that one entity causes the death of another entity indirectly through an intermediary or agent rather than committing the act personally.
-
B.
skillTaught
Indicates that one entity teaches or imparts a particular skill to another entity.
-
C.
kills
Indicates that one entity causes the death of another entity, ending its life.
-
D.
skillSet
Indicates that an entity possesses or is associated with a particular collection of skills or competencies.
-
E.
killsAsPartOfJob
Indicates that one entity kills another as a regular or expected duty within their professional role or occupation.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32d7dfd188190b03e9b4151a4d3d8 |
completed | April 18, 2026, 7:06 a.m. |
| PD | Predicate disambiguation | batch_69e227048d608190a4205eae3117629a |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24556c1348190902a4d116c3137d9 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:10 a.m.