Triple
T4266030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ra |
E96825
|
entity |
| Predicate | transliterationVariant |
P5923
|
FINISHED |
| Object | Re |
E427611
|
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: Re | Statement: [Ra, transliterationVariant, Re]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Re Context triple: [Ra, transliterationVariant, Re]
-
A.
Re
chosen
Re is the ancient Egyptian sun god, a major deity associated with creation, kingship, and the daily journey of the sun across the sky.
-
B.
RE
RE is the two-letter ISO 3166-1 alpha-2 country code assigned to the French overseas department and region of Réunion.
-
C.
RE
RE is the common abbreviation for the British Army’s Corps of Royal Engineers, responsible for military engineering and technical support.
-
D.
RE
RE is the abbreviation for RegioExpress, a category of regional express trains commonly used in European rail transport.
-
E.
Ren
Ren is a central character in Margaret Atwood’s dystopian MaddAddam trilogy, known for her experiences as a sex worker and survivor in a bioengineered, post-apocalyptic world.
- 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_69b34543f06c8190915ebb1a4574ffa9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34fcc383c81908e17da7cbc86a630 |
completed | March 12, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c71c9b488190abbca16d3ea70ae8 |
completed | March 14, 2026, 8:37 p.m. |
Created at: March 12, 2026, 11:07 p.m.