Triple
T34863103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahdi |
E1004933
|
entity |
| Predicate | notMentionedExplicitlyIn |
P119944
|
FINISHED |
| Object | Quran |
—
|
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: Quran | Statement: [Mahdi, notMentionedExplicitlyIn, Quran]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notMentionedExplicitlyIn Context triple: [Mahdi, notMentionedExplicitlyIn, Quran]
-
A.
notMentionedByNameIn
chosen
Indicates that an entity is present or relevant in a context but is not explicitly referred to by its proper name within that context.
-
B.
notDescribedAs
Indicates that an entity is explicitly not characterized, labeled, or referred to using a particular description or term.
-
C.
mentionedButUnseen
Indicates that an entity is referred to or talked about within a context but does not actually appear or become directly observable there.
-
D.
notObservedIn
Indicates that a particular entity, event, or property has not been detected, recorded, or seen within a specified context, dataset, or environment.
-
E.
didNotExplicitlyUseTerm
Indicates that an entity performed an action or produced content without directly or specifically using a particular term.
- 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_69f76dbb678081909a247b9b5e1a73ac |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.