Triple
T658715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chennai English |
E11705
|
entity |
| Predicate | hasGrammarInfluenceFrom |
P4183
|
FINISHED |
| Object | Tamil word order in some sentences |
—
|
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: Tamil word order in some sentences | Statement: [Chennai English, hasGrammarInfluenceFrom, Tamil word order in some sentences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGrammarInfluenceFrom Context triple: [Chennai English, hasGrammarInfluenceFrom, Tamil word order in some sentences]
-
A.
hasLexicalInfluenceOn
Indicates that one linguistic element (such as a word, phrase, or lexicon) has affected or shaped the form, usage, or meaning of another linguistic element.
-
B.
influencedLanguage
chosen
Indicates that one language has had an effect on the development, structure, or usage of another language.
-
C.
hasInfluentialGrammarian
Indicates that an entity is associated with, or characterized by, a grammarian who has significant influence or authority in matters of grammar.
-
D.
hasGrammaticalSimilarityTo
Indicates that two linguistic elements share similar grammatical structure, form, or function.
-
E.
hasGrammarDifferenceFrom
Indicates that two linguistic items differ from each other in their grammatical form, structure, or rules of usage.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0f55f7481909e052a25bd12d455 |
completed | March 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69a49d1406ec8190abf546549264c85d |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.