Triple
T35967367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sīrat ʿAntar |
E1040180
|
entity |
| Predicate | portraysValue |
P49090
|
FINISHED |
| Object | bravery |
—
|
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: bravery | Statement: [Sīrat ʿAntar, portraysValue, bravery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysValue Context triple: [Sīrat ʿAntar, portraysValue, bravery]
-
A.
portraysState
Indicates that one entity visually or symbolically represents or depicts the condition, status, or situation of another entity.
-
B.
portraysProduct
Indicates that one entity visually or narratively represents, depicts, or features a particular product.
-
C.
portraysPositively
Indicates that one entity represents or depicts another entity in a favorable or positive manner.
-
D.
portraysRelation
Indicates that one entity depicts, represents, or acts in the role of another entity within some medium or context.
-
E.
portrayalFeature
chosen
Indicates that one entity serves as a characteristic, aspect, or attribute highlighted in the depiction or representation of 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_69f76e26b21081909fd9ffb3aff6c77a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff63e6b61081909c648bf0ff279481 |
completed | May 9, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69ff6381867881908ae0545df4b71df5 |
completed | May 9, 2026, 4:40 p.m. |
Created at: May 3, 2026, 4:07 p.m.