Triple
T31674642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Article 23 of the United Nations Charter |
E808365
|
entity |
| Predicate | originallySpecifiedNumberOfMembers |
P9077
|
FINISHED |
| Object | 11 |
—
|
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: 11 | Statement: [Article 23 of the United Nations Charter, originallySpecifiedNumberOfMembers, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originallySpecifiedNumberOfMembers Context triple: [Article 23 of the United Nations Charter, originallySpecifiedNumberOfMembers, 11]
-
A.
originalNumberOfMembers
chosen
Indicates the initial total count of members in a group or organization before any changes such as additions or removals.
-
B.
numberOfMembersDeterminedBy
Indicates that the quantity of members in one entity is defined or constrained by another entity or factor.
-
C.
hasMaximumNumberOfMembers
Indicates that there is an upper limit on how many members can be associated with a given entity.
-
D.
lastKnownNumberOfMembers
Indicates the most recently recorded count of members associated with an entity.
-
E.
minimumNumberOfMembers
Indicates the smallest allowable or required number of members that must be present or involved in a given context or group.
- 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_69f348dcf5d48190ac25b1365ae717a8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a0117b6539c8190be7d231e891fe546 |
completed | May 10, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_6a011762f7ec8190afc884b92419d33f |
completed | May 10, 2026, 11:40 p.m. |
Created at: April 30, 2026, 11:02 p.m.