Triple
T12765083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Illiyyin |
E305101
|
entity |
| Predicate | contrastedWith |
P278
|
FINISHED |
| Object | Sijjin |
E305100
|
NE 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: Sijjin | Statement: [Illiyyin, contrastedWith, Sijjin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sijjin Context triple: [Illiyyin, contrastedWith, Sijjin]
-
A.
Sijjin
chosen
Sijjin is an Islamic term referring to a record or register in which the deeds of the wicked are inscribed and a place associated with severe punishment in the Hereafter.
-
B.
Bejae
Bejae is an ancient name historically associated with the Beja people of northeastern Africa, reflecting their early cultural and regional identity.
-
C.
Saiun
Saiun is the Allied reporting name for the Nakajima C6N, a fast and long-range Japanese carrier-based reconnaissance aircraft used during World War II.
-
D.
Jinki
Jinki was a Japanese era name (nengō) of the Nara period, used during the reign of Empress Genshō.
-
E.
Seiyun
Seiyun is a historic city in Yemen’s Hadhramaut region, known for its traditional mud-brick architecture and role as a regional cultural and commercial center.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df1ef148190af525532fcb0933b |
completed | April 10, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f684f4e1508190a6f023f1d1dc192e |
completed | May 2, 2026, 11:12 p.m. |
Created at: April 9, 2026, 5:28 p.m.