Triple
T19575842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarabhanga |
E489855
|
entity |
| Predicate | bodyFate |
P24728
|
FINISHED |
| Object | self-immolation in sacrificial fire (as per some traditions) |
—
|
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: self-immolation in sacrificial fire (as per some traditions) | Statement: [Sarabhanga, bodyFate, self-immolation in sacrificial fire (as per some traditions)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bodyFate Context triple: [Sarabhanga, bodyFate, self-immolation in sacrificial fire (as per some traditions)]
-
A.
fate
Indicates that an entity is destined or predetermined to experience a particular outcome or course of events beyond its control.
-
B.
afterlifeFate
Indicates the outcome or condition an entity experiences in the afterlife as a result of its life or actions.
-
C.
eventualFate
chosen
Indicates the ultimate outcome or final state that an entity is destined to reach over time.
-
D.
knowledgeOfFate
Indicates that one entity is aware of or understands the destined or predetermined outcome concerning another entity or event.
-
E.
fateInBooks
Indicates that a character’s destiny, outcome, or predetermined path is described or revealed within written works or books.
- 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e64024c5b08190bbff6df633857874 |
completed | April 20, 2026, 3:03 p.m. |
| PD | Predicate disambiguation | batch_69e514dbdb988190b55931a8138c73e7 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:42 p.m.