Triple
T1473132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord of the worlds |
E27180
|
entity |
| Predicate | correspondsToArabic |
P5923
|
FINISHED |
| Object | Rabb al-ʿālamīn |
—
|
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: Rabb al-ʿālamīn | Statement: [Lord of the worlds, correspondsToArabic, Rabb al-ʿālamīn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToArabic Context triple: [Lord of the worlds, correspondsToArabic, Rabb al-ʿālamīn]
-
A.
hasNameInArabic
Indicates that an entity is associated with a specific name expressed in the Arabic language.
-
B.
alternativeTransliteration
chosen
Indicates that one written form represents an alternative way of transliterating the same original text or name into another script or orthography.
-
C.
languageEquivalent
Indicates that two linguistic expressions convey the same meaning or function across different languages or language varieties.
-
D.
hasContextualLetterForms
Indicates that the written form of a letter changes shape depending on its surrounding characters or position within a word.
-
E.
equivalentInZapotec
Indicates that two linguistic elements are equivalent in meaning or function within the Zapotec 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_69a496d25d6881909dbd84f86d763992 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c5dc90e481908a4935f266bc7850 |
completed | March 1, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69a4c48350d88190a81bd149103f93e3 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:01 p.m.