Triple
T28834252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lubban ash-Sharqiya |
E728133
|
entity |
| Predicate | hasArabicDefiniteArticleForm |
P5228
|
FINISHED |
| Object | al-Lubban ash-Sharqiya |
—
|
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: al-Lubban ash-Sharqiya | Statement: [Lubban ash-Sharqiya, hasArabicDefiniteArticleForm, al-Lubban ash-Sharqiya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArabicDefiniteArticleForm Context triple: [Lubban ash-Sharqiya, hasArabicDefiniteArticleForm, al-Lubban ash-Sharqiya]
-
A.
hasDefiniteArticle
chosen
Indicates that the referenced entity or term is accompanied by a definite article (such as "the") in the given context.
-
B.
usesDefiniteArticlePosition
Indicates that a definite article appears in a specific syntactic or positional slot relative to another element in the expression.
-
C.
hasGivenNameFormInArabic
Indicates that an entity has a specific given-name form expressed in the Arabic language.
-
D.
hasOpeningWordsArabic
Indicates that an entity (such as a text, document, or work) has specific opening words expressed in the Arabic language.
-
E.
endsWithArabic
Indicates that one entity’s content or representation terminates with Arabic script or characters.
- 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_69f0319dc6088190bbfaa206d40ed74a |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f7626667f48190ad90867eb67ec582 |
completed | May 3, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f76175d6608190b60b268e20f49ed9 |
completed | May 3, 2026, 2:53 p.m. |
Created at: April 28, 2026, 6:38 a.m.