Triple
T8009805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ata ibn Abi Rabah |
E186455
|
entity |
| Predicate | generationRelativeToMuhammad |
P80542
|
FINISHED |
| Object | second generation (Tabiun) |
—
|
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: second generation (Tabiun) | Statement: [Ata ibn Abi Rabah, generationRelativeToMuhammad, second generation (Tabiun)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: generationRelativeToMuhammad Context triple: [Ata ibn Abi Rabah, generationRelativeToMuhammad, second generation (Tabiun)]
-
A.
timeWithMuhammad
Indicates that one entity spends or has spent time together with Muhammad.
-
B.
ageDifferenceWithMuhammad
Indicates the age difference between a given person and Muhammad.
-
C.
caliphOrder
Indicates that one entity holds the position of caliph immediately before or after another entity in a historical or religious succession order.
-
D.
birthYearHijri
Indicates the year of an entity’s birth expressed in the Hijri (Islamic) calendar.
-
E.
distanceFromMecca
Indicates the measured spatial distance between a given location and the city of Mecca.
- F. None of above. chosen
Provenance (4 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_69ca82abaffc8190ab8af79cdbc31ab3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3d6f76408190a1312369521a187a |
completed | March 31, 2026, 3:20 a.m. |
| PD | Predicate disambiguation | batch_69cb048c9f488190b4fb8917a9c21bc5 |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14bcbbc0819094a98e7ffffb7a40 |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:19 p.m.