Triple
T5583049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Narasimha |
E146684
|
entity |
| Predicate | boonCircumvention |
P64890
|
FINISHED |
| Object | neither man nor animal |
—
|
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: neither man nor animal | Statement: [Narasimha, boonCircumvention, neither man nor animal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: boonCircumvention Context triple: [Narasimha, boonCircumvention, neither man nor animal]
-
A.
boonDetails
Indicates the specific terms, conditions, or characteristics associated with a granted benefit or favor within the relationship or action.
-
B.
designedToAvoid
Indicates that something was intentionally created or configured in a way that prevents or minimizes a particular outcome, condition, or interaction.
-
C.
diversionMethod
Indicates the method or tactic used to distract, mislead, or redirect attention or resources away from a primary target or activity.
-
D.
hasBypass
Indicates that one entity includes or is equipped with an alternative route or mechanism that circumvents or avoids another entity or process.
-
E.
avoidsRoute
Indicates that an entity deliberately does not use or travel along a particular route.
- 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_69c0090287a08190b4098411effe970c |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0208333f08190bf0049b6bdd280f5 |
completed | March 22, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69c01b16b9bc8190ab0b945507d90e05 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f4032408190a4f0d2eb21ebd870 |
completed | March 22, 2026, 4:56 p.m. |
Created at: March 22, 2026, 3:37 p.m.