Triple
T32932252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carson Drew |
E842428
|
entity |
| Predicate | oftenHelpsWith |
P90956
|
FINISHED |
| Object | mystery investigations |
—
|
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: mystery investigations | Statement: [Carson Drew, oftenHelpsWith, mystery investigations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenHelpsWith Context triple: [Carson Drew, oftenHelpsWith, mystery investigations]
-
A.
oftenHelps
chosen
Indicates that one entity frequently provides assistance or support to another.
-
B.
sometimesHelps
Indicates that one entity provides help or assistance to another on some occasions but not consistently.
-
C.
especiallyHelpsWhen
Indicates that one entity is particularly beneficial or effective in assisting another entity or situation under certain conditions or circumstances.
-
D.
helpsIn
Indicates that one entity provides assistance, support, or aid to another entity in performing or achieving a particular task, activity, or goal.
-
E.
laterHelps
Indicates that one entity provides help or assistance to another at a subsequent time rather than immediately.
- 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_69f34948adfc8190a937f1f622783c0b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd05ba6b2c81909c62b46237d10365 |
completed | May 7, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69fd03039e48819082b6e12c5453885a |
completed | May 7, 2026, 9:24 p.m. |
Created at: May 1, 2026, 1:20 a.m.