Triple
T1316552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Nations General Assembly resolution 217 A (III) |
E28116
|
entity |
| Predicate | abstainingStatesCount |
P5056
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [United Nations General Assembly resolution 217 A (III), abstainingStatesCount, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: abstainingStatesCount Context triple: [United Nations General Assembly resolution 217 A (III), abstainingStatesCount, 8]
-
A.
requiresAbstentionFrom
Indicates that one entity imposes or necessitates refraining from a specific action, behavior, or substance by another entity.
-
B.
abstentions
chosen
Indicates that certain eligible participants chose not to cast a vote or express a position in a decision-making process.
-
C.
hasElectoralVotes
Indicates that a political entity (such as a state or district) possesses a specified number of votes in an electoral system used to choose an officeholder.
-
D.
numberOfElectors
Indicates the total count of electors associated with a given entity or context.
-
E.
numberOfStatesRepresented
Indicates how many distinct states are represented or covered in a given context or 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_69a498532c3481909223b74af2e578df |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c175079481909077cf11ed72d6fa |
completed | March 1, 2026, 10:45 p.m. |
| PD | Predicate disambiguation | batch_69a4beebcb348190964bd7215811942c |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.