Triple
T2242372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toleration Act 1689 |
E49424
|
entity |
| Predicate | typeOfToleration |
P35662
|
FINISHED |
| Object | conditional toleration |
—
|
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: conditional toleration | Statement: [Toleration Act 1689, typeOfToleration, conditional toleration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfToleration Context triple: [Toleration Act 1689, typeOfToleration, conditional toleration]
-
A.
tolerates
Indicates that one entity endures, accepts, or allows the presence, behavior, or condition of another entity without intervening to stop or change it.
-
B.
typeOfRule
Indicates that one rule is classified as a specific kind or category of another, more general rule.
-
C.
typeOfCondition
chosen
Indicates that one condition is a specific kind, category, or subtype of another condition.
-
D.
tollingType
Indicates the specific method or basis by which a toll, fee, or charge is applied or calculated in a given context.
-
E.
saltTolerance
Indicates the degree to which an entity can withstand or function under saline (high-salt) conditions.
- 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_69a88aa979788190ad6500f1d8eee2fc |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0c017548190a71fb4a0e2a8189f |
completed | March 7, 2026, 6:08 a.m. |
| PD | Predicate disambiguation | batch_69abbdb160248190aa75b38f11ad8602 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.