Triple
T14651141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babette Gladney |
E343986
|
entity |
| Predicate | drugUseMotivation |
P21011
|
FINISHED |
| Object | to cope with fear of death |
—
|
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: to cope with fear of death | Statement: [Babette Gladney, drugUseMotivation, to cope with fear of death]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drugUseMotivation Context triple: [Babette Gladney, drugUseMotivation, to cope with fear of death]
-
A.
attitudeTowardDrugs
Indicates an entity’s stance, opinion, or disposition regarding the use or presence of drugs.
-
B.
drugUseHistory
Indicates that an entity has a recorded past or ongoing pattern of using drugs.
-
C.
usedSubstance
Indicates that an entity has consumed, applied, or otherwise made use of a particular substance.
-
D.
reasonForUse
chosen
Indicates that one entity specifies the justification, purpose, or motivation for using another entity.
-
E.
associatedWithSubstance
Indicates that one entity has a relevant connection or involvement with a particular substance, such as use, presence, exposure, or composition.
- 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb517e7648190b9fc73d6cdbb68de |
completed | April 14, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69de6576f0208190aa94d995e797ac38 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:27 a.m.