Triple
T3981747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgian French |
E85772
|
entity |
| Predicate | hasDifferenceIn |
P34645
|
FINISHED |
| Object | lexicon |
—
|
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: lexicon | Statement: [Belgian French, hasDifferenceIn, lexicon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDifferenceIn Context triple: [Belgian French, hasDifferenceIn, lexicon]
-
A.
hasLexicalDifferencesWith
chosen
Indicates that two linguistic items differ from each other in their word choice or lexical form.
-
B.
hasDelta
Indicates that there is a change, difference, or deviation between two related states, values, or versions of something.
-
C.
differenceFromStates
Indicates that one state or condition is distinct from, or deviates in some way from, another state or condition.
-
D.
hasGrammarDifferenceFrom
Indicates that two linguistic items differ from each other in their grammatical form, structure, or rules of usage.
-
E.
isDistinctFrom
Indicates that two entities are not identical and can be clearly distinguished from one another.
- 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_69aed93908348190a26c8aaf4fab3e86 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa3ef7ac8190abe02f440ff83c43 |
completed | March 9, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69aef8f492ac819089dbb9436dbcdd2b |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:33 p.m.