Triple
T25804310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Starkweather killing spree |
E649920
|
entity |
| Predicate | accompliceAge |
P159285
|
FINISHED |
| Object | 14 |
—
|
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: 14 | Statement: [Charles Starkweather killing spree, accompliceAge, 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accompliceAge Context triple: [Charles Starkweather killing spree, accompliceAge, 14]
-
A.
perpetratorAge
Indicates the age of the individual who committed or is alleged to have committed an offense or harmful act.
-
B.
ageAtTimeOfAccusation
Indicates the age a person was at the specific time when an accusation was made against them.
-
C.
partnerInCrime
Indicates a relationship where two or more entities collaborate closely in committing or planning wrongful, illicit, or mischievous acts together.
-
D.
ageAtTimeOfConvictionInStory
Indicates the age a person was at the specific time they were convicted within the context or timeline of the story.
-
E.
ageAtArrest
Indicates the age a person was at the time they were arrested.
- 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_69e7ab35d264819095367f7e80c983ff |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f5ffcdc66c8190a7aa2f1bdfe01f98 |
completed | May 2, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69f4938b960081909b53c074a3e0c7c2 |
completed | May 1, 2026, 11:50 a.m. |
| PDg | Predicate description generation | batch_69f497b8abb88190bb672cf6907c4b8d |
completed | May 1, 2026, 12:08 p.m. |
Created at: April 22, 2026, 7:01 a.m.