Triple
T30746066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalimat-i-Maknúnih |
E782818
|
entity |
| Predicate | containsNumberOfSayings |
P50925
|
FINISHED |
| Object | 71 Arabic passages |
—
|
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: 71 Arabic passages | Statement: [Kalimat-i-Maknúnih, containsNumberOfSayings, 71 Arabic passages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsNumberOfSayings Context triple: [Kalimat-i-Maknúnih, containsNumberOfSayings, 71 Arabic passages]
-
A.
includesSaying
Indicates that one entity (such as a text, speech, or communication) contains or incorporates a particular saying, phrase, or quoted expression.
-
B.
numberOfAphorisms
chosen
Indicates the quantity or count of aphorisms associated with a given entity.
-
C.
hasSayingTheme
Indicates that a saying, proverb, or quoted expression is about or centers on a particular theme or subject.
-
D.
containsNumberOfPoems
Indicates that one entity includes or specifies a particular quantity of poems associated with it.
-
E.
hasVersesBy
Indicates a relationship where a work, such as a song or poem, contains verses authored or written by a specific creator.
- 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_69f224af8d8481908bea03890c5618be |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ff2d22ffb48190ae58ddf3c7e02869 |
completed | May 9, 2026, 12:48 p.m. |
| PD | Predicate disambiguation | batch_69ff2ac2e1c4819096cc64e94aef2ff0 |
completed | May 9, 2026, 12:38 p.m. |
Created at: April 29, 2026, 8:38 p.m.