Triple
T38009925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard Carstone |
E948336
|
entity |
| Predicate | healthEffectOf |
P19730
|
FINISHED |
| Object | Jarndyce and Jarndyce lawsuit |
—
|
NE NERFINISHED |
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: Jarndyce and Jarndyce lawsuit | Statement: [Richard Carstone, healthEffectOf, Jarndyce and Jarndyce lawsuit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: healthEffectOf Context triple: [Richard Carstone, healthEffectOf, Jarndyce and Jarndyce lawsuit]
-
A.
healthEffect
chosen
Indicates the impact or consequence that one entity has on the health or well-being of another.
-
B.
healthType
Indicates the specific category or classification of health status or condition associated with an entity.
-
C.
healthAttribute
Indicates that one entity specifies or characterizes a particular health-related property, condition, or quality of another entity.
-
D.
healthHabit
Indicates a relationship where an entity regularly engages in a behavior or practice that affects its health or well-being.
-
E.
healthTheme
Indicates that the subject is associated with, focuses on, or is characterized by a particular health-related topic or theme.
- 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_69f76efb4b10819092c8c2ba28ac06a8 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcc7338120819081cb46547d60f2cb |
completed | May 7, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69fcc58566a0819082d5ea36e03bf0c6 |
completed | May 7, 2026, 5:01 p.m. |
Created at: May 3, 2026, 4:20 p.m.