Triple
T30513894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The January Man |
E776504
|
entity |
| Predicate | hasSerialKillerTheme |
P136388
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The January Man, hasSerialKillerTheme, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSerialKillerTheme Context triple: [The January Man, hasSerialKillerTheme, true]
-
A.
hasSerialKiller
Indicates that one entity is a serial killer associated with, responsible for, or targeting another entity.
-
B.
hasSerialKillerElement
chosen
Indicates that something includes, involves, or is characterized by an aspect, theme, or component related to a serial killer.
-
C.
hasMurderer
Indicates that one entity is the person who committed the murder of another entity.
-
D.
hasKillerProtagonist
Indicates that the main character in a work is a killer or has committed killing as a defining aspect of their role.
-
E.
hasKiller
Indicates that one entity is the killer or cause of death of another entity.
- 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_69f2249a155c8190b1d512106007e9bb |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69feaa483fcc81909d8a46b38a8717bf |
completed | May 9, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69fea8c9d45c81908ccc8619e5fefac1 |
completed | May 9, 2026, 3:23 a.m. |
Created at: April 29, 2026, 8:16 p.m.