Triple
T21709533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ianuarius |
E535863
|
entity |
| Predicate | correspondsToNumber |
P128211
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Ianuarius, correspondsToNumber, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToNumber Context triple: [Ianuarius, correspondsToNumber, 1]
-
A.
correspondsToEnglishLetter
Indicates that one entity is the English alphabet letter that matches, represents, or is equivalent to the other entity.
-
B.
correspondsWith
Indicates that two entities are in mutual alignment or agreement, such that one matches, parallels, or is equivalent to the other in a specified respect.
-
C.
containsNumber
Indicates that one entity includes or has at least one numeric value or digit within it.
-
D.
value1CorrespondsTo
chosen
Indicates that one value is directly associated with, matches, or maps to another value in a defined correspondence.
-
E.
hasOppositeNumberForm
Indicates that one entity is represented by a number form that is the opposite (e.g., additive vs. subtractive, positive vs. negative, or otherwise contrastive) of the number form used to represent the other entity.
- 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_69e0c46b44c0819088ab883ebd44e0e8 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efb5321d34819091f3cd03f7b407c0 |
completed | April 27, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69e6969113cc8190ab69855ef5667e4b |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:46 p.m.