Triple
T6112561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abhimanyu |
E136279
|
entity |
| Predicate | didNotKnow |
P22661
|
FINISHED |
| Object | how to exit the Chakravyuha |
—
|
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: how to exit the Chakravyuha | Statement: [Abhimanyu, didNotKnow, how to exit the Chakravyuha]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: didNotKnow Context triple: [Abhimanyu, didNotKnow, how to exit the Chakravyuha]
-
A.
ignorantOf
chosen
Indicates that one entity lacks knowledge or awareness of another entity or of some specific fact, topic, or situation.
-
B.
didNotBecome
Indicates that an expected or potential change of state, role, or condition between entities did not occur.
-
C.
didNotHold
Indicates that an expected event, condition, or relationship failed to occur or be valid.
-
D.
hadNo
Indicates that one entity completely lacked or did not possess another entity, attribute, or relationship.
-
E.
doesNot
Indicates that a specified entity lacks, refrains from, or fails to perform a particular action or exhibit a particular property in relation to another entity or context.
- 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_69c0089ea6f88190b349be53e04b4f5f |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05bbde2048190909aa3a8097bcf93 |
completed | March 22, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c049f80e2081909b7d84a104cda68d |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:13 p.m.