Triple
T4725358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Eight Conference |
E104869
|
entity |
| Predicate | numberOfMemberSchoolsAtEnd |
P276
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [Big Eight Conference, numberOfMemberSchoolsAtEnd, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMemberSchoolsAtEnd Context triple: [Big Eight Conference, numberOfMemberSchoolsAtEnd, 8]
-
A.
hasNumberOfSchools
Indicates the quantity of schools associated with a given entity.
-
B.
hasNumberOfMemberInstitutions
chosen
Indicates the quantitative count of member institutions associated with a given entity.
-
C.
numberOfMemberOrganizations
Indicates the total count of organizations that are members of a given group, association, or umbrella entity.
-
D.
numberOfFullMembers
Indicates the total count of entities that hold full membership status within a specified group or organization.
-
E.
numberOfUniversities
Indicates the quantity of universities associated with a given 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_69bd43ed84648190ae0b7ee8e8d00482 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6220071881909670c89d072ffb6d |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:18 p.m.