Triple
T7942229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ian Brady |
E184416
|
entity |
| Predicate | occupationBeforeCrimes |
P28984
|
FINISHED |
| Object | stock clerk |
—
|
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: stock clerk | Statement: [Ian Brady, occupationBeforeCrimes, stock clerk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationBeforeCrimes Context triple: [Ian Brady, occupationBeforeCrimes, stock clerk]
-
A.
earlierOccupation
chosen
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
B.
hasPerpetratorOccupation
Indicates that the occupation or job role of the perpetrator involved in an act or incident is being specified.
-
C.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
D.
characterFormerOccupation
Indicates that a character previously held a specific occupation but no longer does.
-
E.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
- 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_69ca8291c2008190b1b8832c87814bcf |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b0c16b8819093c5d1719cd65ee3 |
completed | March 31, 2026, 3:10 a.m. |
| PD | Predicate disambiguation | batch_69cae93526d081909303265bf60419fd |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:09 p.m.