Triple
T37965012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Countess Elisabeth Dobrzensky de Dobrzenicz |
E947115
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object |
Princess Teresa of Orléans-Braganza
Princess Teresa of Orléans-Braganza is a Brazilian-born princess of the former imperial House of Orléans-Braganza, a dynastic branch linked to both the Brazilian and French royal families.
|
E2261450
|
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: Princess Teresa of Orléans-Braganza | Statement: [Countess Elisabeth Dobrzensky de Dobrzenicz, child, Princess Teresa of Orléans-Braganza]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Princess Teresa of Orléans-Braganza Triple: [Countess Elisabeth Dobrzensky de Dobrzenicz, child, Princess Teresa of Orléans-Braganza]
Generated description
Princess Teresa of Orléans-Braganza is a Brazilian-born princess of the former imperial House of Orléans-Braganza, a dynastic branch linked to both the Brazilian and French royal families.
Provenance (5 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_69f76ef7062c819091bfacb7e83aa1e0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbbdf4b9a081908f36f2c678e7d400 |
completed | May 6, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41852b27208190bb5325e6fd76b7ba |
completed | June 28, 2026, 8:33 p.m. |
| NEDg | Description generation | batch_6a41896173ec8190b8efe271478129fd |
completed | June 28, 2026, 8:51 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a41898996cc8190a9d3a6c4229b7bb4 |
completed | June 28, 2026, 8:52 p.m. |
Created at: May 3, 2026, 4:20 p.m.