Triple
T23904065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linkoln |
E601135
|
entity |
| Predicate | hasCharacterDifferenceFrom |
P16425
|
FINISHED |
| Object | Lincoln:usesLetter"k"InsteadOf"c" |
—
|
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: Lincoln:usesLetter"k"InsteadOf"c" | Statement: [Linkoln, hasCharacterDifferenceFrom, Lincoln:usesLetter"k"InsteadOf"c"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCharacterDifferenceFrom Context triple: [Linkoln, hasCharacterDifferenceFrom, Lincoln:usesLetter"k"InsteadOf"c"]
-
A.
hasLexicalDifferencesWith
Indicates that two linguistic items differ from each other in their word choice or lexical form.
-
B.
hasGrammarDifferenceFrom
Indicates that two linguistic items differ from each other in their grammatical form, structure, or rules of usage.
-
C.
hasDistinctCharacterSet
chosen
Indicates that two compared items use different sets of characters, with no character set being a subset or duplicate of the other.
-
D.
differIn
Indicates that two entities are not the same in at least one specified aspect, attribute, or value.
-
E.
hasDifferentFateOfCharacter
Indicates that two characters experience distinct outcomes or destinies within a narrative or scenario.
- 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_69e295364a488190bcac702e9bb7f764 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cde0674c8190a5e1ce0315ae83cd |
completed | April 29, 2026, 9:22 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:26 p.m.