Triple
T10416537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aegon |
E245530
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object | Ennia |
E248271
|
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: Ennia | Statement: [Aegon, foundedBy, Ennia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ennia Context triple: [Aegon, foundedBy, Ennia]
-
A.
Ennia
chosen
Ennia was a former Dutch insurance company that later became part of Aegon through a merger.
-
B.
Ennia
Ennia is a historical figure known as the founder of the ancient city of Aegon.
-
C.
Enna
Enna is a historic hilltop city in central Sicily, Italy, known for its elevated position and panoramic views over the island.
-
D.
Stryama
Stryama is a river in Bulgaria that flows through the central part of the country before joining the Maritsa River.
-
E.
Enide
Enide is a heroine of Arthurian romance, best known as the loyal and courageous wife of the knight Erec in medieval French literature.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea108fec8190819423630888fa2b |
completed | April 7, 2026, 11:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fc0dd480819082edcc49a245ad4f |
completed | April 9, 2026, 7:20 p.m. |
Created at: April 6, 2026, 12:10 p.m.