Triple
T4685309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hiranyakashipu |
E103906
|
entity |
| Predicate | killedHow |
P2115
|
FINISHED |
| Object | torn apart by Narasimha’s claws |
—
|
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: torn apart by Narasimha’s claws | Statement: [Hiranyakashipu, killedHow, torn apart by Narasimha’s claws]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: killedHow Context triple: [Hiranyakashipu, killedHow, torn apart by Narasimha’s claws]
-
A.
killedBy
Indicates that one entity caused the death of another entity.
-
B.
killedDuring
Indicates that one entity caused the death of another entity in the course of, or as part of, a specified event or time period.
-
C.
killedAt
Indicates that a killing event occurred at a specific location or time associated with the entities involved.
-
D.
killedFamilyOf
Indicates that one entity caused the death of one or more members of another entity’s family.
-
E.
usedMethodOfKilling
chosen
Indicates that one entity employed a particular method or means to carry out a killing of another entity.
- 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_69bd43debbf08190b4bc372e286ec234 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6217e0088190836570522e324dc6 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:16 p.m.