Triple
T5024573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vibhishana |
E112941
|
entity |
| Predicate | adviceContent |
P52897
|
FINISHED |
| Object | Return Sita to Rama and make peace |
—
|
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: Return Sita to Rama and make peace | Statement: [Vibhishana, adviceContent, Return Sita to Rama and make peace]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adviceContent Context triple: [Vibhishana, adviceContent, Return Sita to Rama and make peace]
-
A.
advises
Indicates that one entity provides guidance, recommendations, or counsel to another entity.
-
B.
topicOfAdvice
Indicates that one entity is the subject or focus about which advice is being given by another entity.
-
C.
articleContent
Indicates that one entity is the textual or media content that makes up the body of another entity, typically an article or document.
-
D.
madeRecommendation
chosen
Indicates that one entity has suggested or advised another entity to consider a particular option, action, or choice.
-
E.
curatesContentFrom
Indicates that one entity selects, organizes, and presents content that originates from another entity.
- 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd736852e88190b69d6561ca7604c3 |
completed | March 20, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69bd71509e9c8190a60c1d8d04936a12 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:36 p.m.