Triple
T8526976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banu Makhzum |
E201841
|
entity |
| Predicate | roleInMecca |
P83155
|
FINISHED |
| Object | military leadership of Quraysh |
—
|
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: military leadership of Quraysh | Statement: [Banu Makhzum, roleInMecca, military leadership of Quraysh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInMecca Context triple: [Banu Makhzum, roleInMecca, military leadership of Quraysh]
-
A.
roleInArabia
Indicates that an entity holds or held a specific role, position, or function within the context of Arabia.
-
B.
roleInMedina
Indicates the specific function, position, or responsibility an entity holds within the context of Medina.
-
C.
positionOnKaaba
Indicates that one entity occupies a specific location or placement on the surface or structure of the Kaaba.
-
D.
numberOfPilgrimagesToMecca
Indicates the count of times an entity has undertaken a pilgrimage to Mecca.
-
E.
roleInHadith
Indicates the specific function, position, or participation an entity has within the context or transmission of a hadith.
- 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_69ca83228b24819085d22e7dc99f5d94 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe6477100819081fa20cb6b8ea3d7 |
completed | March 31, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69cbd10f64b4819080859057c19e58f0 |
completed | March 31, 2026, 1:50 p.m. |
| PDg | Predicate description generation | batch_69cbe30d453481908f897ed2b06e7534 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:16 p.m.