Triple
T9496892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ernest Hoschedé |
E229029
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Hoschedé |
E230477
|
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: Hoschedé | Statement: [Ernest Hoschedé, hasFamilyName, Hoschedé]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hoschedé Context triple: [Ernest Hoschedé, hasFamilyName, Hoschedé]
-
A.
Hoschedé
chosen
Hoschedé is a French surname notably associated with the family closely linked to Impressionist painter Claude Monet.
-
B.
Maenza
Maenza is a small historic town in the Lazio region of central Italy, known for its medieval architecture and hilltop setting.
-
C.
Maurepas
Maurepas is a commune in the Yvelines department in the Île-de-France region of north-central France, known as a residential suburb southwest of Paris.
-
D.
Dehéries
Dehéries is a small commune in the Nord department of northern France.
-
E.
Ménerbes
Ménerbes is a picturesque hilltop village in southeastern France’s Provence region, renowned for its historic stone architecture, vineyards, and views over the Luberon countryside.
- 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd95ecf4148190aa8f4733980166ae |
completed | April 1, 2026, 10:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d12d3aafb88190ac53289039bca88a |
completed | April 4, 2026, 3:24 p.m. |
Created at: March 30, 2026, 7:56 p.m.