Triple
T32853029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Ghaffar |
E840303
|
entity |
| Predicate | conveysSenseOf |
P4340
|
FINISHED |
| Object | repeated forgiveness |
—
|
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: repeated forgiveness | Statement: [Al-Ghaffar, conveysSenseOf, repeated forgiveness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conveysSenseOf Context triple: [Al-Ghaffar, conveysSenseOf, repeated forgiveness]
-
A.
hasSense
Indicates that an entity possesses or is associated with a particular sensory perception, meaning, or interpretation.
-
B.
primarySense
Indicates that one sense or meaning of an entity is designated as its main or most central sense among possible alternatives.
-
C.
senses
Indicates that an entity perceives or detects another entity or stimulus through one of its senses.
-
D.
conveysStyle
Indicates that one entity expresses, communicates, or embodies a particular style through its form, behavior, or presentation.
-
E.
hasConnotation
chosen
Indicates that one entity carries an implied or associated meaning, tone, or emotional nuance in relation to another 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_69f349412c78819084459850e11d29f7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: May 1, 2026, 1:17 a.m.