Triple
T1434950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georges Cuvier |
E30539
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Jean
Jean is a given name associated here with Georges Cuvier, the influential French naturalist and zoologist who founded the field of comparative anatomy and helped establish extinction as a scientific fact.
|
E180189
|
NE FINISHED |
How this triple was built (4 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: Jean | Statement: [Georges Cuvier, givenName, Jean]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jean Context triple: [Georges Cuvier, givenName, Jean]
-
A.
Jean
Jean is the given first name of Henry Dunant, the Swiss humanitarian who founded the Red Cross and received the first Nobel Peace Prize.
-
B.
Jean
Jean is a small unincorporated community in Clark County, Nevada, known primarily as a roadside stop and gateway to Las Vegas for travelers from California.
-
C.
Alexis
Alexis is a given name most famously borne by the French political thinker and historian Alexis de Tocqueville.
-
D.
Marie
Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
-
E.
Renée
Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Jean Triple: [Georges Cuvier, givenName, Jean]
Generated description
Jean is a given name associated here with Georges Cuvier, the influential French naturalist and zoologist who founded the field of comparative anatomy and helped establish extinction as a scientific fact.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jean Target entity description: Jean is a given name associated here with Georges Cuvier, the influential French naturalist and zoologist who founded the field of comparative anatomy and helped establish extinction as a scientific fact.
-
A.
Jean
Jean is the given first name of Henry Dunant, the Swiss humanitarian who founded the Red Cross and received the first Nobel Peace Prize.
-
B.
Jean
Jean is a small unincorporated community in Clark County, Nevada, known primarily as a roadside stop and gateway to Las Vegas for travelers from California.
-
C.
Alexis
Alexis is a given name most famously borne by the French political thinker and historian Alexis de Tocqueville.
-
D.
Marie
Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
-
E.
Renée
Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
- F. None of above. chosen
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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c500a9888190a16fbb1ec97a79c9 |
completed | March 1, 2026, 11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad46878b3c8190ac46d5b9f0fd12e7 |
completed | March 8, 2026, 9:51 a.m. |
| NEDg | Description generation | batch_69ad470cdcd8819094bfc66d0cb38295 |
completed | March 8, 2026, 9:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad47692f288190892e48c2bd87df90 |
completed | March 8, 2026, 9:54 a.m. |
Created at: March 1, 2026, 8 p.m.