Triple
T20613612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarah (Book of Tobit) |
E506508
|
entity |
| Predicate | helpedBy |
P24359
|
FINISHED |
| Object | archangel Raphael |
—
|
NE NERFINISHED |
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 Raphael | Statement: [Sarah (Book of Tobit), helpedBy, archangel Raphael]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: archangel Raphael Context triple: [Sarah (Book of Tobit), helpedBy, archangel Raphael]
-
A.
Raphael (archangel)
chosen
Raphael is an archangel in Judeo-Christian tradition, often associated with healing and guidance, notably appearing in the deuterocanonical Book of Tobit.
-
B.
Archangel Uriel
Archangel Uriel is a revered archangel in various religious and mystical traditions, often associated with divine wisdom, illumination, and prophetic insight.
-
C.
Seraphim
Seraphim are the highest-ranking class of angels in Christian angelology, traditionally associated with fiery devotion and the worship of God.
-
D.
Arcángel
Arcángel is a Puerto Rican-American reggaeton and Latin trap singer and songwriter known for his influential role in the urban Latin music scene.
-
E.
Gabriel
Gabriel is a common masculine given name of Hebrew origin, widely used in many cultures and languages.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4bb2b4081908fa4a72444120f35 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aada19e481909363428ceda67603 |
completed | April 20, 2026, 10:38 p.m. |
Created at: April 16, 2026, 11:41 a.m.