Triple
T25859631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IceCube Collaboration |
E651445
|
entity |
| Predicate | hasInstitutionCountApprox |
P276
|
FINISHED |
| Object | over 50 institutions |
—
|
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: over 50 institutions | Statement: [IceCube Collaboration, hasInstitutionCountApprox, over 50 institutions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInstitutionCountApprox Context triple: [IceCube Collaboration, hasInstitutionCountApprox, over 50 institutions]
-
A.
hasNumberOfMemberInstitutions
chosen
Indicates the quantitative count of member institutions associated with a given entity.
-
B.
hasInstitutions
Indicates that one entity possesses, contains, or is associated with one or more institutions.
-
C.
hasInstitutionalPresenceIn
Indicates that an institution maintains an established presence, such as operations, offices, or activities, within a specified location or region.
-
D.
hasApproximateStudents
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
E.
affiliatedCollegeCount
Indicates the number of colleges that are formally affiliated 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_69e7ab3a199c81909227cb964cacfe24 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f969b4cc8190afb473a2d8b110bc |
completed | May 3, 2026, 7:29 a.m. |
Created at: April 22, 2026, 8:05 a.m.