Triple
T24811951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | al-Najāshī |
E620813
|
entity |
| Predicate | grantedRefugeTo |
P157841
|
FINISHED |
| Object | early Muslim emigrants from Mecca |
—
|
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: early Muslim emigrants from Mecca | Statement: [al-Najāshī, grantedRefugeTo, early Muslim emigrants from Mecca]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grantedRefugeTo Context triple: [al-Najāshī, grantedRefugeTo, early Muslim emigrants from Mecca]
-
A.
takenAsRefugeBy
Indicates that one entity is used or relied upon by another entity as a place or source of safety, protection, or refuge.
-
B.
designatedAsRefuge
Indicates that an entity has been officially assigned or recognized as a refuge or place of protection.
-
C.
tookRefugeWith
Indicates that one entity sought safety, protection, or shelter by going to and staying with another entity.
-
D.
hasNotableRefuge
Indicates that an entity is associated with a particularly important or well-known place of refuge or shelter.
-
E.
wasRefugee
Indicates that an entity previously lived as a refugee, having been forced to leave their home country due to conflict, persecution, or disaster.
- 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_69e2fabf26bc8190b191faac8f67065b |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f453035f508190be83a3d521723acf |
completed | May 1, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69f44d6ef33081908f5d36ba1ae5f473 |
completed | May 1, 2026, 6:51 a.m. |
| PDg | Predicate description generation | batch_69f45300bd488190bb1d4160f5534ef6 |
completed | May 1, 2026, 7:15 a.m. |
Created at: April 18, 2026, 4:50 a.m.