Triple
T29028844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ungeduldig (No. 4) |
E737668
|
entity |
| Predicate | hasNumberWithinSet |
P187912
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Ungeduldig (No. 4), hasNumberWithinSet, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberWithinSet Context triple: [Ungeduldig (No. 4), hasNumberWithinSet, 4]
-
A.
containsNumber
Indicates that one entity includes or has at least one numeric value or digit within it.
-
B.
hasDigitSet
Indicates that an entity is associated with a specific set or collection of digits.
-
C.
hasNumberInStructure
Indicates that an entity’s structure includes or contains a specific numerical value or component.
-
D.
hasNumberWithinWork
Indicates that a specific number or numeric value is contained, referenced, or used within a particular work (such as a document, publication, or creative piece).
-
E.
cardNumberInSet
chosen
Indicates that a specific card has a particular number or position within a defined set or collection of cards.
- 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_69f077ef00fc81909325f084ad37c035 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: April 28, 2026, 9:54 a.m.