Triple
T30516532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tawûsê Melek |
E776582
|
entity |
| Predicate | moralCharacterInYazidism |
P47751
|
FINISHED |
| Object | benevolent |
—
|
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: benevolent | Statement: [Tawûsê Melek, moralCharacterInYazidism, benevolent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralCharacterInYazidism Context triple: [Tawûsê Melek, moralCharacterInYazidism, benevolent]
-
A.
hasMoralCharacteristic
chosen
Indicates that an entity possesses a particular moral quality, trait, or ethical attribute.
-
B.
hasMoralArchetype
Indicates that an entity exemplifies or is characterized by a particular moral pattern, role, or ethical archetype.
-
C.
judgmentCharacterizationInIslamicSources
Indicates how a person, action, or event is evaluated or characterized in Islamic religious or legal sources.
-
D.
moralPortrayal
Indicates how an entity is depicted in terms of moral qualities, such as virtue, vice, or ethical standing, within a given context.
-
E.
moralBelief
Indicates that an agent holds a normative judgment about what is right, wrong, good, or bad in a given context.
- 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_69f2249b23c4819087fa85496d92f43f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f69dfdda708190be290c7bec205445 |
completed | May 3, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f69d1a37e081908d1d86b90ff502bd |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 8:16 p.m.