Triple
T1289122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surah Al-Baqarah |
E27504
|
entity |
| Predicate | containsVerseNumber |
P18696
|
FINISHED |
| Object | 255 |
—
|
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: 255 | Statement: [Surah Al-Baqarah, containsVerseNumber, 255]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsVerseNumber Context triple: [Surah Al-Baqarah, containsVerseNumber, 255]
-
A.
hasVerseCount
Indicates that an entity (such as a text or section) is associated with a specific number of verses it contains.
-
B.
verseNumber
chosen
Indicates the specific numbered position of a verse within an ordered sequence, such as in a chapter, song, or poem.
-
C.
approximateNumberOfVerses
Indicates an estimated or approximate count of verses associated with an entity.
-
D.
hasMultipleVerses
Indicates that something, typically a song, poem, or text, consists of more than one verse.
-
E.
mostVersesChapter
Indicates that a chapter has the highest number of verses compared to all other chapters within the same collection or text.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0d4dfb081908c8825d6062b1d99 |
completed | March 1, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69a4bee41ca08190b0ad6f7ea40c0b62 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.