Triple
T10794390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saraswati Samman |
E254664
|
entity |
| Predicate | awardedForLanguages |
P63553
|
FINISHED |
| Object | Assamese |
—
|
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: Assamese | Statement: [Saraswati Samman, awardedForLanguages, Assamese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardedForLanguages Context triple: [Saraswati Samman, awardedForLanguages, Assamese]
-
A.
awardNameLanguage
Indicates the language in which the name of an award is expressed.
-
B.
awardLanguage
chosen
Indicates that an award is given specifically for works or achievements in a particular language.
-
C.
winnerLanguage
Indicates that the associated language is the one used by, or officially recognized for, the winner in a given contest, award, or competitive event.
-
D.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
E.
languageOfAwardAdministration
Indicates the language used to administer, manage, or conduct the award process.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732f878648190be5e25c56a7511cf |
completed | April 9, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69d6f316940c819092a96c429629fdef |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:17 p.m.