Triple
T1129400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bastet |
E24792
|
entity |
| Predicate | parent |
P120
|
FINISHED |
| Object | Ra |
E96825
|
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: Ra | Statement: [Bastet, parent, Ra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ra Context triple: [Bastet, parent, Ra]
-
A.
Ra
chosen
Ra is the ancient Egyptian sun god, revered as a supreme creator deity and central figure in Pharaonic religion and mythology.
-
B.
RA
RA is the commonly used abbreviation for the Royal Regiment of Artillery, a principal artillery branch of the British Army.
-
C.
RA
RA is a prestigious post-nominal title indicating membership as a Royal Academician of the Royal Academy of Arts in London.
-
D.
R
R is a New York City Subway service that runs along the Broadway Line in Manhattan and Queens, providing local transit through key commercial and residential areas.
-
E.
R
R is a widely used open-source programming language and environment focused on statistical computing, data analysis, and graphical visualization.
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bbdea9b88190a88da718bf5c1897 |
completed | March 1, 2026, 10:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac59a82bb8819084f77aff9af653c0 |
completed | March 7, 2026, 5 p.m. |
Created at: March 1, 2026, 7:44 p.m.