Triple
T28544219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abu Muhammad |
E722385
|
entity |
| Predicate | usedAsKunyaOf |
P167898
|
FINISHED |
| Object | Hasan al-Askari |
—
|
NE NERFINISHED |
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: Hasan al-Askari | Statement: [Abu Muhammad, usedAsKunyaOf, Hasan al-Askari]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsKunyaOf Context triple: [Abu Muhammad, usedAsKunyaOf, Hasan al-Askari]
-
A.
usesKunya
chosen
Indicates that one entity refers to or identifies another entity by a kunya (a teknonymic nickname, typically based on "father/mother of" someone).
-
B.
kunya
Indicates the honorific or respectful name by which a person is addressed or referred to, typically reflecting esteem, modesty, or social standing.
-
C.
hasEndonym
Indicates that an entity has a name or designation used by native speakers or within its own local language or community.
-
D.
usedAsNamesakeFor
Indicates that one entity serves as the source or inspiration for the name given to another entity.
-
E.
usedAsNationalLanguageBaseFor
Indicates that one language serves as the primary linguistic foundation or reference for defining or standardizing another language used at the national level.
- 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_69f01a5e42348190b1ffbca26e739c84 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f78c61ed4c8190ad84c918fa9af55a |
completed | May 3, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69f78b8cb3a881909ebaac1b503988c2 |
completed | May 3, 2026, 5:53 p.m. |
Created at: April 28, 2026, 3:37 a.m.