Triple
T4402822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twenty-one Conditions for admission |
E93655
|
entity |
| Predicate | hasNumberOfConditions |
P56046
|
FINISHED |
| Object | 21 |
—
|
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: 21 | Statement: [Twenty-one Conditions for admission, hasNumberOfConditions, 21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfConditions Context triple: [Twenty-one Conditions for admission, hasNumberOfConditions, 21]
-
A.
hasCondition
Indicates that an entity possesses, experiences, or is affected by a particular condition or state.
-
B.
hasConjunction
Indicates that two or more entities are linked together by a coordinating conjunction, forming a combined or joint relationship.
-
C.
hasPrecedingCondition
Indicates that one condition occurs or exists before another condition in time or sequence.
-
D.
hasNumberOfTerms
Indicates the quantity of distinct terms or elements associated with a given entity or expression.
-
E.
hasNumberOfCasesApprox
Indicates that an entity is associated with an approximate (not exact) count of cases.
- F. None of above. chosen
Provenance (4 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_69b345158c748190a2c040fce2da9980 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b352d08a0c8190ac6c125df40eca75 |
completed | March 12, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69b34f5b36a881909bf2e970aa523390 |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b3509997208190933f167f7e20ccfa |
completed | March 12, 2026, 11:47 p.m. |
Created at: March 12, 2026, 11:28 p.m.