Triple
T9473640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diana Goodman |
E228455
|
entity |
| Predicate | hasMentalIllness |
P1005
|
FINISHED |
| Object | bipolar disorder |
—
|
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: bipolar disorder | Statement: [Diana Goodman, hasMentalIllness, bipolar disorder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMentalIllness Context triple: [Diana Goodman, hasMentalIllness, bipolar disorder]
-
A.
diagnosedWith
chosen
Indicates that a subject has been identified, typically by a medical professional, as having a particular disease or medical condition.
-
B.
hasPossibleSymptom
Indicates that an entity (such as a condition or disease) may be associated with a particular symptom that can potentially occur.
-
C.
hasAssociatedDisease
Indicates that an entity is linked to, or commonly occurs with, a particular disease or medical condition.
-
D.
hasHistoryOf
Indicates that an entity has a documented prior occurrence or background of a specified condition, event, or state.
-
E.
hasIdentityIssues
Indicates that an entity experiences confusion, uncertainty, or conflict regarding its own identity or sense of self.
- 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_69ca847162c48190b079076c9595513c |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ff0afd08190871b68a88fdbff2b |
completed | April 1, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69cca55f01b081908dc0f12eaa45f832 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:54 p.m.