Triple
T15530520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laurent |
E370200
|
entity |
| Predicate | psychologicalStateAfterCrime |
P119041
|
FINISHED |
| Object | haunted by guilt |
—
|
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: haunted by guilt | Statement: [Laurent, psychologicalStateAfterCrime, haunted by guilt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: psychologicalStateAfterCrime Context triple: [Laurent, psychologicalStateAfterCrime, haunted by guilt]
-
A.
hasMotiveOfCriminals
Indicates that the specified motive is attributed to or associated with the criminals in question.
-
B.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
C.
perpetratorStatus
Indicates the role or condition of an individual in relation to committing or being responsible for a specific harmful or criminal act.
-
D.
settingOfCrime
Indicates the location or environment in which a crime takes place.
-
E.
targetOfCrime
Indicates that the subject is the person, organization, or entity against whom the referenced crime is committed.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0414773548190b3311515f9d957dd |
completed | April 16, 2026, 1:54 a.m. |
| PD | Predicate disambiguation | batch_69ded28ab0588190a47a9090d1238707 |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded57165288190979b7acb71ad5145 |
completed | April 15, 2026, 12:01 a.m. |
Created at: April 10, 2026, 4:05 a.m.