Triple
T19026333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anugita |
E465618
|
entity |
| Predicate | timeOfDialogue |
P133610
|
FINISHED |
| Object | after the Kurukshetra war |
—
|
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: after the Kurukshetra war | Statement: [Anugita, timeOfDialogue, after the Kurukshetra war]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeOfDialogue Context triple: [Anugita, timeOfDialogue, after the Kurukshetra war]
-
A.
dialogueType
Indicates the specific kind or category of dialogue occurring between entities (e.g., question-answer, negotiation, instruction).
-
B.
dialogue
Indicates that two or more entities are engaged in an exchange of spoken or written communication with each other.
-
C.
dialoguePosition
Indicates the relative placement or ordering of an utterance or turn within a dialogue or conversational sequence.
-
D.
dialogueContext
Indicates the situational and conversational background in which a dialogue occurs, including prior exchanges and relevant circumstances that shape its interpretation.
-
E.
numberOfDialogues
Indicates the total count of dialogues associated with or occurring between the referenced entities.
- 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_69d8dd025c188190a1d81f5b4ec7e2c6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d73cace0819096bdac6dc8c17253 |
completed | April 20, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69e4a2fd80c081908237317a3a883e1c |
completed | April 19, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69e4ad8f6f7c8190af645bf08823ee2b |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 12:02 p.m.