Triple
T17681682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DP |
E440784
|
entity |
| Predicate | numberOfSubjectsRequired |
P101171
|
FINISHED |
| Object | six subjects |
—
|
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: six subjects | Statement: [DP, numberOfSubjectsRequired, six subjects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSubjectsRequired Context triple: [DP, numberOfSubjectsRequired, six subjects]
-
A.
numberOfCourses
Indicates the quantity of courses associated with a given entity.
-
B.
subjectCount
chosen
Indicates the number of subjects associated with or involved in a given entity or context.
-
C.
requiresSubjectsAtLevel
Indicates that an entity depends on other subjects being present or qualified at a specified level in order for a condition, action, or state to be valid or achievable.
-
D.
requiresEducationIn
Indicates that one entity necessitates that another entity possess education or formal training in a specified field or discipline.
-
E.
writtenExamSubjectsInclude
Indicates that the set of subjects specified is included among the subjects covered by a particular written exam.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e470445b3881908bb0930b986089f7 |
completed | April 19, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69e3cde3673c8190a889e14ba1f07dc1 |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 10:01 a.m.