Triple
T17952961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aditya Hridayam |
E448875
|
entity |
| Predicate | benefitDescribed |
P112305
|
FINISHED |
| Object | removal of sorrow |
—
|
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: removal of sorrow | Statement: [Aditya Hridayam, benefitDescribed, removal of sorrow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitDescribed Context triple: [Aditya Hridayam, benefitDescribed, removal of sorrow]
-
A.
benefitAppliesTo
Indicates that a particular benefit is applicable to, or valid for, a specified entity or context.
-
B.
benefitCharacteristic
Indicates that one entity possesses a quality or feature that provides an advantage, usefulness, or positive effect to another entity.
-
C.
benefitsAre
Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
-
D.
benefitProtection
Indicates that one entity provides protective advantages or safeguards that benefit another entity.
-
E.
benefitsMayInclude
chosen
Indicates that one entity lists or specifies possible advantages, gains, or positive outcomes that another entity may receive.
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4afad61f481908b34cd24de88983c |
completed | April 19, 2026, 10:34 a.m. |
| PD | Predicate disambiguation | batch_69e3f8f2bd088190b1e22ad4d9cc8b13 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:21 a.m.