Triple
T38415429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Sanskrit Language (1786 discourse) |
E901587
|
entity |
| Predicate | mentionsLanguage |
P2177
|
FINISHED |
| Object | Sanskrit |
—
|
NE NERFINISHED |
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: Sanskrit | Statement: [The Sanskrit Language (1786 discourse), mentionsLanguage, Sanskrit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mentionsLanguage Context triple: [The Sanskrit Language (1786 discourse), mentionsLanguage, Sanskrit]
-
A.
usesLanguageFor
Indicates that an entity employs a particular language as a tool or medium to perform some activity, function, or purpose.
-
B.
eligibleLanguage
Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
-
C.
includesLanguage
chosen
Indicates that one entity contains, supports, or makes use of a specified language as part of its content, functionality, or representation.
-
D.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
-
E.
languageEmphasizes
Indicates that one language or linguistic system places particular focus, importance, or prominence on a specific feature, concept, or element compared to others.
- 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_69f76e61e79c81908b787d83b46ab92b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcd1499e2c81909bafd84dc4810f45 |
completed | May 7, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69fcccf024ec819086383ffbb6cfc036 |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 3, 2026, 4:31 p.m.