Triple
T1378699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surah Al-Anfal |
E29285
|
entity |
| Predicate | chronologicalOrderApproximate |
P23880
|
FINISHED |
| Object | 88 |
—
|
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: 88 | Statement: [Surah Al-Anfal, chronologicalOrderApproximate, 88]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chronologicalOrderApproximate Context triple: [Surah Al-Anfal, chronologicalOrderApproximate, 88]
-
A.
chronologicallyClassifiedAs
Indicates that something is assigned to or placed within a specific time period or chronological category.
-
B.
chronologicalPosition
Indicates the relative ordering of one event or entity in time with respect to another.
-
C.
chronologicallyAfter
Indicates that one event or state occurs later in time than another.
-
D.
chronologicalFunction
Indicates a temporal relationship where one event or state functions to order, structure, or position another within a sequence of time.
-
E.
chronologicalOrderInSeries
chosen
Indicates that one entity appears earlier or later than another within an ordered sequence or series.
- 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c3187f248190a5813274b0ef944d |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4befcabdc8190a9f05d002603f81c |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.