Triple
T35366202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guyanese English |
E1021635
|
entity |
| Predicate | lexiconSharesWith |
P35118
|
FINISHED |
| Object | Standard English |
—
|
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: Standard English | Statement: [Guyanese English, lexiconSharesWith, Standard English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lexiconSharesWith Context triple: [Guyanese English, lexiconSharesWith, Standard English]
-
A.
sharesLexiconWith
chosen
Indicates that two entities use or are associated with the same set of lexical items, vocabulary, or word inventory.
-
B.
sharesTermWith
Indicates that two entities are associated with or contain at least one common term (e.g., word, label, or keyword) in their representations.
-
C.
lexiconStatus
Indicates the current state or condition of a lexical item within a lexicon, such as whether it is active, deprecated, provisional, or otherwise classified.
-
D.
sharesLanguageWith
Indicates that two entities use at least one common language for communication.
-
E.
sharesSpellingWith
Indicates that two entities have identical or substantially identical written forms (i.e., they are spelled the same way).
- 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_69f76df000488190ab7c97f565677055 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79533b88c8190934ec4cb21770e24 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.