Triple
T25489830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keralaputra |
E638807
|
entity |
| Predicate | referredToIn |
P8581
|
FINISHED |
| Object | studies of Mauryan-era South India |
—
|
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: studies of Mauryan-era South India | Statement: [Keralaputra, referredToIn, studies of Mauryan-era South India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: referredToIn Context triple: [Keralaputra, referredToIn, studies of Mauryan-era South India]
-
A.
referredTo
Indicates that one entity has mentioned, directed attention to, or cited another entity as a point of reference.
-
B.
alsoRefersTo
Indicates that one term, label, or identifier is used as an alternative designation for the same entity or concept as another.
-
C.
isReferencedIn
chosen
Indicates that one entity is cited, mentioned, or otherwise referred to within another entity.
-
D.
notablyRefersTo
Indicates that one entity makes a particularly significant or noteworthy reference to another entity, beyond a routine or incidental mention.
-
E.
refersSpecificallyTo
Indicates that one entity makes an explicit, precise reference to another particular entity, distinguishing it from more general or ambiguous references.
- 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_69e75dbabeac8190bab30628f8b799d4 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 21, 2026, 2:34 p.m.