Triple
T18590002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albert DeSalvo |
E454338
|
entity |
| Predicate | timePeriodOfCriminalActivity |
P104728
|
FINISHED |
| Object | early 1960s |
—
|
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: early 1960s | Statement: [Albert DeSalvo, timePeriodOfCriminalActivity, early 1960s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timePeriodOfCriminalActivity Context triple: [Albert DeSalvo, timePeriodOfCriminalActivity, early 1960s]
-
A.
endTimeOfCriminalActivity
Indicates the specific time at which a criminal activity or offense comes to an end.
-
B.
timeframeOfCrimes
chosen
Indicates the period or span of time during which the crimes occurred or were committed.
-
C.
activeYearsInCrime
Indicates the span of time during which an entity was actively involved in criminal activities.
-
D.
startDateOfCriminalEvents
Indicates the date on which the referenced criminal events began or were first initiated.
-
E.
peakIncarcerationPeriod
Indicates the time period during which incarceration levels for the referenced entity were at their highest.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e545b4a2a0819098047ee81278bd9d |
completed | April 19, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69e478c98d4c81909d37a0e72c6e7bd0 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:44 a.m.