Triple
T26996974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judiciary of Nepal |
E680001
|
entity |
| Predicate | hasSpecialBody |
P178272
|
FINISHED |
| Object | Judicial Council of Nepal |
—
|
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: Judicial Council of Nepal | Statement: [Judiciary of Nepal, hasSpecialBody, Judicial Council of Nepal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpecialBody Context triple: [Judiciary of Nepal, hasSpecialBody, Judicial Council of Nepal]
-
A.
hasBodyOf
Indicates that one entity possesses, contains, or is composed of the physical body or main substance of another entity.
-
B.
hasBodyPlanType
Indicates that an organism possesses a particular overall structural or morphological body plan type.
-
C.
hasBodyPlanFeature
Indicates that an organism’s body plan includes a specific structural or morphological feature.
-
D.
haveBody
Indicates that one entity possesses, contains, or is associated with another entity as its body or main physical/content component.
-
E.
hasTopBody
Indicates that one entity possesses or is characterized by a primary upper body section.
- F. None of above. chosen
Provenance (4 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_69eeeb52908c8190bd246244686aa455 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
| PDg | Predicate description generation | batch_69f70e854b9c8190a3416e2189e17742 |
completed | May 3, 2026, 8:59 a.m. |
Created at: April 27, 2026, 6:55 a.m.