Triple
T9422507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yazid I |
E227189
|
entity |
| Predicate | viewedNegativelyBy |
P21336
|
FINISHED |
| Object | many Shia Muslims |
—
|
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: many Shia Muslims | Statement: [Yazid I, viewedNegativelyBy, many Shia Muslims]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewedNegativelyBy Context triple: [Yazid I, viewedNegativelyBy, many Shia Muslims]
-
A.
negativeMarking
Indicates that an entity assigns or receives a penalty, deduction, or unfavorable score in response to a particular action, performance, or condition.
-
B.
negativeType
Indicates that one entity is classified as a negative, undesirable, or disfavored type in relation to another or within a given context.
-
C.
viewedBySomeAs
chosen
Indicates that at least one observer or group perceives or interprets an entity in a particular way or role.
-
D.
negates
Indicates that one entity denies, contradicts, or renders false the assertion, state, or effect expressed by another.
-
E.
criticizedFor
Indicates that one entity expresses disapproval or negative judgment of another entity specifically because of a particular action, quality, or outcome.
- 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_69ca8436ba308190903e470776d2d893 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd6c27c8cc8190a11162c10c33b17e |
completed | April 1, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69cca550777c819094e1851a6127cbbc |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:48 p.m.