Triple
T6826864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melchior |
E157036
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object | Magi |
E29144
|
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: Magi | Statement: [Melchior, memberOf, Magi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magi Context triple: [Melchior, memberOf, Magi]
-
A.
Magi
chosen
The Magi are the wise men or kings from the East in the New Testament who visit the infant Jesus, traditionally bearing gifts of gold, frankincense, and myrrh.
-
B.
The Magic
The Magic is a self-help book by Rhonda Byrne that expands on the themes of The Secret by focusing on the transformative power of gratitude.
-
C.
La Maga
La Maga is a mysterious, free-spirited woman who embodies emotional intuition and existential uncertainty in Julio Cortázar’s novel "Rayuela" ("Hopscotch").
-
D.
El Mago
El Mago is the nickname of Argentine former professional tennis player Guillermo Coria, renowned for his exceptional clay-court skills and speed.
-
E.
Jadu
Jadu is a small town in western Libya situated in the Nafusa Mountains, known for its Amazigh (Berber) heritage and strategic highland location.
- 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_69c6882a5b5c8190917a7db9ed36bad1 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d58583a4819099edbf753c7c7087 |
completed | March 27, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c751130fd48190af94e632dcf0b798 |
completed | March 28, 2026, 3:54 a.m. |
Created at: March 27, 2026, 2:18 p.m.