Triple
T11758937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hudson family murders |
E279602
|
entity |
| Predicate | hasConvictionDate |
P9179
|
FINISHED |
| Object | 2012-05-11 |
—
|
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: 2012-05-11 | Statement: [Hudson family murders, hasConvictionDate, 2012-05-11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConvictionDate Context triple: [Hudson family murders, hasConvictionDate, 2012-05-11]
-
A.
dateOfConviction
chosen
Indicates the specific calendar date on which a person or entity was formally found guilty of an offense.
-
B.
hasFirstConviction
Indicates that an entity has received its first legal conviction for an offense.
-
C.
convictionYear
Indicates the calendar year in which an entity was formally convicted of an offense.
-
D.
convictedOf
Indicates that a person or entity has been found guilty of committing a specified offense or crime through a formal legal process.
-
E.
hasHadCriminalConviction
Indicates that an entity has previously been found guilty of a criminal offense through a legal process.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a5220f148190ae60d1941a579ab6 |
completed | April 10, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69d88a829fe481909cc5431de7d6058e |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.