Triple
T15678914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ghadir Khumm |
E377520
|
entity |
| Predicate | hasArabicPhrase |
P114902
|
FINISHED |
| Object | “Man kuntu mawlahu fa Aliyyun mawlahu” |
—
|
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: “Man kuntu mawlahu fa Aliyyun mawlahu” | Statement: [Ghadir Khumm, hasArabicPhrase, “Man kuntu mawlahu fa Aliyyun mawlahu”]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArabicPhrase Context triple: [Ghadir Khumm, hasArabicPhrase, “Man kuntu mawlahu fa Aliyyun mawlahu”]
-
A.
hasKeyTermArabic
chosen
Indicates that an entity is associated with a specific key term expressed in the Arabic language.
-
B.
hasNameInArabic
Indicates that an entity is associated with a specific name expressed in the Arabic language.
-
C.
hasOpeningWordsArabic
Indicates that an entity (such as a text, document, or work) has specific opening words expressed in the Arabic language.
-
D.
hasArabicNumeral
Indicates that an entity is associated with, represented by, or expressed using an Arabic numeral.
-
E.
hasGivenNameFormInArabic
Indicates that an entity has a specific given-name form expressed in the Arabic language.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f2f1640819086efd5a73bb9734a |
completed | April 16, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69deda8b36a4819081cb5708fe77ef51 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:16 a.m.