Triple
T6717834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaiser Wilhelm Society |
E153315
|
entity |
| Predicate | numberOfInstitutesAtPeak |
P72850
|
FINISHED |
| Object | over 30 |
—
|
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 30 | Statement: [Kaiser Wilhelm Society, numberOfInstitutesAtPeak, over 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfInstitutesAtPeak Context triple: [Kaiser Wilhelm Society, numberOfInstitutesAtPeak, over 30]
-
A.
numberOfUniversities
Indicates the quantity of universities associated with a given entity.
-
B.
numberOfResearchCentres
Indicates the quantity of research centres associated with a given entity.
-
C.
institutes
Indicates that an entity establishes, initiates, or formally sets up another entity, process, or system.
-
D.
memberCountAtPeak
Indicates the highest number of members that an entity (such as a group or organization) has had at any point in time.
-
E.
numberOfDistrictsPeak
Indicates the maximum number of districts that an entity reaches or has at its highest point over a given period or context.
- 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_69c68809b4608190a2509ddb5ab87f05 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d12765a48190b485176dc2ffa0fa |
completed | March 27, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69c6d08c5d348190a29dee668c398e70 |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d11fab808190b18160ff3829fcc6 |
completed | March 27, 2026, 6:49 p.m. |
Created at: March 27, 2026, 2:07 p.m.