Triple
T14470148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tayran Ababil |
E358816
|
entity |
| Predicate | genreOfTextMention |
P22130
|
FINISHED |
| Object | Meccan surah |
—
|
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: Meccan surah | Statement: [Tayran Ababil, genreOfTextMention, Meccan surah]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfTextMention Context triple: [Tayran Ababil, genreOfTextMention, Meccan surah]
-
A.
literaryGenreOfWork
chosen
Indicates that a work belongs to or is classified under a particular literary genre.
-
B.
genreOfAssociatedPerson
Indicates that a particular genre is associated with a given person, such as an artist, author, or performer.
-
C.
genreDocumented
Indicates that a work’s genre has been formally recorded or documented.
-
D.
genreOfCharacter
Indicates that a character belongs to or is associated with a particular genre (such as fantasy, horror, or comedy).
-
E.
genreOfWorkAbout
Indicates that a work is about a particular genre, expressing that the work’s subject matter or focus concerns that genre.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91f969788190a5114f92d7159aae |
completed | April 14, 2026, 7:14 p.m. |
| PD | Predicate disambiguation | batch_69de5c42bd3c81909a62acf30cc24d1e |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:20 a.m.