Triple
T21477820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | al-Azam |
E529908
|
entity |
| Predicate | notableUsageType |
P2529
|
FINISHED |
| Object | part of throne names of rulers |
—
|
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: part of throne names of rulers | Statement: [al-Azam, notableUsageType, part of throne names of rulers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableUsageType Context triple: [al-Azam, notableUsageType, part of throne names of rulers]
-
A.
notableUse
Indicates that something is prominently or famously used by a particular entity, context, or for a specific purpose.
-
B.
notableTypeOf
Indicates that one entity is a particularly prominent, well-known, or exemplary instance or subtype of another entity.
-
C.
notableServiceType
Indicates that the subject is associated with a particular type or category of service that is especially notable or significant.
-
D.
notableTargetType
Indicates that the subject is notable or significant specifically in relation to entities of the given target type.
-
E.
usageType
chosen
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
- 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_69e0c459acb481909bb6ee452a0045c7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea1951fc8190910f634327aa5c3f |
completed | April 23, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69e631ec1d048190b6da97da8222e413 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:20 p.m.