Triple
T6385123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ragnar |
E143680
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Ragge |
E590310
|
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: Ragge | Statement: [Ragnar, hasDiminutive, Ragge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ragge Context triple: [Ragnar, hasDiminutive, Ragge]
-
A.
Ragge
chosen
Ragge is a familiar nickname commonly used for the Scandinavian given name Ragnar.
-
B.
Rhagae
Rhagae is the ancient name of the historic city near modern-day Tehran in Iran, once a major center of the Median and later Persian empires.
-
C.
Raka
Raka is a renowned Afrikaans narrative poem by N. P. van Wyk Louw that explores themes of civilization, barbarism, and moral conflict through an allegorical tale.
-
D.
Rallo
Rallo is a young, mischievous character from the animated television series "The Cleveland Show," known for his precocious attitude and comedic antics.
-
E.
Raidurg
Raidurg is a rapidly developing commercial and residential neighborhood in Hyderabad’s IT hub, known for its proximity to major tech parks and infrastructure in the Cyberabad area.
- 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_69c008dac1ec81909cef8157ccd69962 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0686764648190864163d390db292d |
completed | March 22, 2026, 10:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c640b7e89881908e1c39d45e8a8473 |
completed | March 27, 2026, 8:32 a.m. |
Created at: March 22, 2026, 4:34 p.m.