Triple
T5648575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max Mayfield |
E124443
|
entity |
| Predicate | hasTraumaRelatedTo |
P41242
|
FINISHED |
| Object | abuse by Billy Hargrove |
—
|
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: abuse by Billy Hargrove | Statement: [Max Mayfield, hasTraumaRelatedTo, abuse by Billy Hargrove]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraumaRelatedTo Context triple: [Max Mayfield, hasTraumaRelatedTo, abuse by Billy Hargrove]
-
A.
trauma
chosen
Indicates that an entity has experienced a deeply distressing or harmful event or series of events that cause lasting psychological or emotional impact.
-
B.
hasInjuries
Indicates that an entity has sustained one or more physical or bodily injuries.
-
C.
traumaLevel
Indicates the degree or severity of trauma experienced or present in relation to an entity or event.
-
D.
hasInjuredPerson
Indicates that an entity has a person who has been harmed or injured associated with it.
-
E.
injuredIn
Indicates that an entity sustained an injury as a result of a specified event, situation, or action.
- 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_69c00825df388190a58742fa9b1aa33d |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022d1534c8190ac4828e44300fb91 |
completed | March 22, 2026, 5:11 p.m. |
| PD | Predicate disambiguation | batch_69c01b2168508190b64b355cf50034ad |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:42 p.m.