Triple
T5649839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michele |
E124474
|
entity |
| Predicate | associatedWithFigure |
P1183
|
FINISHED |
| Object | Archangel Michael |
E50376
|
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: Archangel Michael | Statement: [Michele, associatedWithFigure, Archangel Michael]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Archangel Michael Context triple: [Michele, associatedWithFigure, Archangel Michael]
-
A.
Saint Michael
chosen
Saint Michael is an archangel in Christian, Jewish, and Islamic traditions, revered as a protector, leader of the heavenly hosts, and vanquisher of evil.
-
B.
Seraphim
Seraphim are the highest-ranking class of angels in Christian angelology, traditionally associated with fiery devotion and the worship of God.
-
C.
Raphael (archangel)
Raphael is an archangel in Judeo-Christian tradition, often associated with healing and guidance, notably appearing in the deuterocanonical Book of Tobit.
-
D.
Angel
Angel is a given name used across various cultures, often associated with spiritual or celestial connotations.
-
E.
Angel
"Angel" is a 1937 romantic comedy film directed by Ernst Lubitsch, known for its sophisticated wit and starring Marlene Dietrich, Herbert Marshall, and Melvyn Douglas.
- 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_69c00825df388190a58742fa9b1aa33d |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022d2ed648190a5152c8668cbda02 |
completed | March 22, 2026, 5:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a14a48948190bde99c4a97fe5fa0 |
completed | March 23, 2026, 2:11 a.m. |
Created at: March 22, 2026, 3:42 p.m.