Triple
T9001485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Exorcist |
E215047
|
entity |
| Predicate | setting |
P1957
|
FINISHED |
| Object | Assiah |
E475780
|
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: Assiah | Statement: [Blue Exorcist, setting, Assiah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Assiah Context triple: [Blue Exorcist, setting, Assiah]
-
A.
Assiah
chosen
Assiah is the Kabbalistic world of action and material existence, representing the lowest of the four spiritual realms in Jewish mysticism.
-
B.
Arnissa
Arnissa is a small town in northern Greece situated close to Lake Vegoritida, known for its scenic lakeside setting and surrounding natural landscape.
-
C.
Juwayriya
Juwayriya was a wife of the Prophet Muhammad and is regarded as one of the Mothers of the Believers in Islamic tradition.
-
D.
Unaizah
Unaizah is a historic oasis city in central Saudi Arabia’s Qassim region, known for its date farms, traditional markets, and cultural heritage.
-
E.
Ijesha
Ijesha are a subgroup of the Yoruba people known for their distinct dialect, cultural traditions, and historical presence in southwestern Nigeria.
- 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6956a6e08190bd3853a7c1c130eb |
completed | April 1, 2026, 12:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0ddb1648190a50f8877218d9883 |
completed | April 3, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:05 p.m.