Triple
T20854301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peeps |
E513439
|
entity |
| Predicate | hasSpellingVariantRelationshipWith |
P457
|
FINISHED |
| Object | Samuel Pepys surname |
—
|
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: Samuel Pepys surname | Statement: [Peeps, hasSpellingVariantRelationshipWith, Samuel Pepys surname]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpellingVariantRelationshipWith Context triple: [Peeps, hasSpellingVariantRelationshipWith, Samuel Pepys surname]
-
A.
hasVariantSpelling
chosen
Indicates that one term is an alternative spelling form of another term.
-
B.
hasVariantReadingsWith
Indicates a relationship where two textual items are linked because they exhibit differing or alternative readings of (typically) the same underlying content.
-
C.
sharesSpellingWith
Indicates that two entities have identical or substantially identical written forms (i.e., they are spelled the same way).
-
D.
hasDistinctOrthographyFrom
Indicates that two written forms are orthographically different from each other, even if they may represent the same or related linguistic content.
-
E.
hasPronunciationDifferenceFrom
Indicates that two linguistic items differ in how they are pronounced.
- 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_69e0b4f5b01081909452f654d2fc3f50 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c3a7113c819087994bcdfe643bc1 |
completed | April 21, 2026, 12:24 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a593f481908beb457c29f1ce73 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:44 p.m.