Triple
T19721294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nityananda |
E473614
|
entity |
| Predicate | relationshipToChaitanya |
P137066
|
FINISHED |
| Object | chief associate |
—
|
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: chief associate | Statement: [Nityananda, relationshipToChaitanya, chief associate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToChaitanya Context triple: [Nityananda, relationshipToChaitanya, chief associate]
-
A.
relationshipToRama
Indicates the specific familial, social, or other relational connection that an entity has to Rama.
-
B.
relationshipWithBharata
Indicates that there exists a specific type of relationship or association between an entity and Bharata.
-
C.
relationshipWithRama
Indicates that there exists some form of relationship or association between an entity and Rama.
-
D.
relationshipToTopa
Indicates a familial or social relationship that an entity has specifically with Topa.
-
E.
associatedWithAcharya
Indicates a relationship in which an entity is connected, linked, or related in some relevant way to an acharya (a spiritual or scholarly teacher).
- 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_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e649f483c481908c6b3114bf9c5934 |
completed | April 20, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69e530438c60819082364c7be3eef6f0 |
completed | April 19, 2026, 7:42 p.m. |
| PDg | Predicate description generation | batch_69e532bbedf081908d801600e2af94a7 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:46 p.m.