Triple
T35200954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeffrey Dahmer |
E1016399
|
entity |
| Predicate | startTimeOfCrimes |
P122778
|
FINISHED |
| Object | 1978 |
—
|
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: 1978 | Statement: [Jeffrey Dahmer, startTimeOfCrimes, 1978]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTimeOfCrimes Context triple: [Jeffrey Dahmer, startTimeOfCrimes, 1978]
-
A.
timeframeOfCrimes
Indicates the period or span of time during which the crimes occurred or were committed.
-
B.
startDateOfCriminalEvents
chosen
Indicates the date on which the referenced criminal events began or were first initiated.
-
C.
temporalCrime
Indicates a temporal relationship between a crime and a time reference, such as when the crime occurred, was planned, or was discovered.
-
D.
endTimeOfCriminalActivity
Indicates the specific time at which a criminal activity or offense comes to an end.
-
E.
timeGapBetweenCrimeAndInvestigation
Indicates the duration of time that elapses between when a crime occurs and when its formal investigation begins.
- 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_69f76dde814c8190a71f60d514a424a4 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a005e8a2f7c819085bfc6f04b866d87 |
completed | May 10, 2026, 10:31 a.m. |
| PD | Predicate disambiguation | batch_6a005de82ef08190a015b385d1d3443c |
completed | May 10, 2026, 10:28 a.m. |
Created at: May 3, 2026, 4:02 p.m.