Triple
T8084125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | largest remainder method |
E188687
|
entity |
| Predicate | canBeAppliedTo |
P1129
|
FINISHED |
| Object | allocation of seats among regions |
—
|
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: allocation of seats among regions | Statement: [largest remainder method, canBeAppliedTo, allocation of seats among regions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeAppliedTo Context triple: [largest remainder method, canBeAppliedTo, allocation of seats among regions]
-
A.
appliesTo
chosen
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
B.
appliesFrom
Indicates that a rule, condition, or effect begins to be applicable starting from a specific point in time or state.
-
C.
appliesAt
Indicates that an action, rule, or condition is relevant to or in effect at a specific location, context, or point in time.
-
D.
appliesToFeature
Indicates that something (such as a rule, constraint, or configuration) is relevant to, or governs, a specific feature.
-
E.
appliesOver
Indicates that one entity’s effect, rule, or condition extends across or is valid for a specified range, domain, or set of entities.
- 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_69ca82b662e88190b9323daab8c28a21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb415e61ac81909e924aea69a7ff77 |
completed | March 31, 2026, 3:37 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:29 p.m.