Triple
T4782270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kumbhakarna |
E106393
|
entity |
| Predicate | sleepCurse |
P59293
|
FINISHED |
| Object | sleeps for long intervals and wakes briefly |
—
|
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: sleeps for long intervals and wakes briefly | Statement: [Kumbhakarna, sleepCurse, sleeps for long intervals and wakes briefly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sleepCurse Context triple: [Kumbhakarna, sleepCurse, sleeps for long intervals and wakes briefly]
-
A.
sleepPattern
Indicates the typical timing, duration, and regularity of an entity’s sleep over a given period.
-
B.
associatedCurse
Indicates that one entity is linked to, affected by, or bears responsibility for a particular curse related to another entity.
-
C.
attemptedCurseReversal
Indicates an action where one entity tried, but did not necessarily succeed, to reverse or undo a curse affecting another entity.
-
D.
scripturalCurse
Indicates that one entity pronounces or embodies a curse upon another as recorded or prescribed in a religious or scriptural context.
-
E.
nightService
Indicates that a service operates or is available during nighttime hours.
- 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_69bd43f4a9588190bf73e20bc27c03cc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd69237f80819090713ed62653fb75 |
completed | March 20, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69bd622be1388190ab5511b589c878c0 |
completed | March 20, 2026, 3:05 p.m. |
| PDg | Predicate description generation | batch_69bd6922407481908565ed0b1dac2b30 |
completed | March 20, 2026, 3:34 p.m. |
Created at: March 20, 2026, 1:22 p.m.