Triple
T2093817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German National Academy of Sciences Leopoldina |
E32732
|
entity |
| Predicate | hasApproximateNumberOfMembers |
P20367
|
FINISHED |
| Object | over 1,500 |
—
|
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 1,500 | Statement: [German National Academy of Sciences Leopoldina, hasApproximateNumberOfMembers, over 1,500]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfMembers Context triple: [German National Academy of Sciences Leopoldina, hasApproximateNumberOfMembers, over 1,500]
-
A.
hasApproximateMemberCount
chosen
Indicates that an entity is associated with a group or collection for which only an estimated or non-exact number of members is known.
-
B.
hasMaximumNumberOfMembers
Indicates that there is an upper limit on how many members can be associated with a given entity.
-
C.
hasCurrentNumberOfMembers
Indicates the current count of members associated with a given entity.
-
D.
numberOfMembersReturned
Indicates the quantity of members that are provided or yielded as a result of an operation or query.
-
E.
numberOfKnownMembers
Indicates the count of members within a group or set whose identities are known or have been explicitly determined.
- 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_69a885eba0708190999696a45cbec816 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba98c32081908a243bc7088a1510 |
completed | March 7, 2026, 5:41 a.m. |
| PD | Predicate disambiguation | batch_69abb7b6274081909df36cd7a7c6a675 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.