Triple
T26106921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ar-Rahman |
E658560
|
entity |
| Predicate | scopeOfMercy |
P159955
|
FINISHED |
| Object | universal |
—
|
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: universal | Statement: [Ar-Rahman, scopeOfMercy, universal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scopeOfMercy Context triple: [Ar-Rahman, scopeOfMercy, universal]
-
A.
scopeOfForgiveness
Indicates the extent or boundaries within which forgiveness is granted or applies between entities.
-
B.
mercyRule
Indicates that a game is ended early because one side has achieved a lead so large that continuing is deemed unnecessary or unsporting.
-
C.
scopeOfDestruction
Indicates the extent or range within which damage or destruction affects entities or areas.
-
D.
forgivenessType
Indicates the specific kind or category of forgiveness that characterizes the relationship or action between entities.
-
E.
timeOfCondemnation
Indicates the specific time at which a condemnation (such as a legal judgment or formal denunciation) occurs or is issued.
- F. None of above. chosen
Provenance (4 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_69ee5bc09c288190bc42a11972841383 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f607782ce48190a57ade3cfe455c89 |
completed | May 2, 2026, 2:17 p.m. |
| PD | Predicate disambiguation | batch_69f5b0021da88190bdd4cf2698c23edf |
completed | May 2, 2026, 8:04 a.m. |
| PDg | Predicate description generation | batch_69f5f6b32a8881909baa0db57b80d56a |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 26, 2026, 7:59 p.m.