Triple
T14821689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sara Tancredi |
E348465
|
entity |
| Predicate | formerAddict |
P62269
|
FINISHED |
| Object | morphine |
—
|
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: morphine | Statement: [Sara Tancredi, formerAddict, morphine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerAddict Context triple: [Sara Tancredi, formerAddict, morphine]
-
A.
addiction
Indicates a compulsive dependence of one entity on a substance, activity, or behavior, typically despite negative consequences and difficulty stopping.
-
B.
isRecoveringAddict
chosen
Indicates that an individual is in the process of recovering from addiction, typically through ongoing treatment, support, or personal efforts to maintain sobriety.
-
C.
hasAddictiveSubstance
Indicates that an entity contains or involves a substance capable of causing addiction in those who use or consume it.
-
D.
hasDrugAddictedProtagonist
Indicates that the work’s main character is portrayed as being addicted to drugs.
-
E.
usedSubstance
Indicates that an entity has consumed, applied, or otherwise made use of a particular substance.
- 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decfe64328819083ce42704cf0602d |
completed | April 14, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69de8c0ef8a4819092d84478b1f56db1 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:51 a.m.