Triple
T27387543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Gävle |
E691421
|
entity |
| Predicate | hasApproximateStaffNumber |
P17907
|
FINISHED |
| Object | ~700 |
—
|
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: ~700 | Statement: [University of Gävle, hasApproximateStaffNumber, ~700]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateStaffNumber Context triple: [University of Gävle, hasApproximateStaffNumber, ~700]
-
A.
employsApproximateNumberOfPeople
chosen
Indicates that an entity employs a roughly estimated or approximate number of people, rather than an exact headcount.
-
B.
hasApproximateNumberOfPeople
Indicates that an entity is associated with an estimated or approximate count of people, rather than an exact number.
-
C.
hasApproximateStudents
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
D.
estimatedMemberCount
Indicates the approximate or predicted number of members associated with an entity.
-
E.
hasNumberOfHumanMembers
Indicates the relationship that specifies how many human members are 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_69ef520386788190bc92cfcd97ebb67a |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
Created at: April 27, 2026, 12:24 p.m.