Triple
T5506041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jamal Lyon |
E144442
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Lyon
Lyon is a major French city known for its rich history, gastronomy, and role as a cultural and economic hub in the Auvergne-Rhône-Alpes region.
|
E15889
|
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: Lyon | Statement: [Jamal Lyon, familyName, Lyon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lyon Context triple: [Jamal Lyon, familyName, Lyon]
-
A.
Lyon
Lyon is a major city in east-central France known for its historical and architectural landmarks, gastronomy, and role as a key economic and cultural center.
-
B.
Lyons
Lyons is a small city in southeastern Georgia, United States, known as the administrative and commercial hub of Toombs County.
-
C.
Lyons
Lyons is a sports team or athletic program associated with Wheaton College, commonly referred to by this shortened name.
-
D.
Clermont-Ferrand
Clermont-Ferrand is a central French city known for its historic cathedral built of black volcanic stone and as the longtime headquarters of the tire company Michelin.
-
E.
Rodez
Rodez is a historic cathedral city in southern France that serves as the capital of the Aveyron department in the Occitanie region.
- 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: Lyon Triple: [Jamal Lyon, familyName, Lyon]
Generated description
Lyon is a major French city known for its rich history, gastronomy, and role as a cultural and economic hub in the Auvergne-Rhône-Alpes region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lyon Target entity description: Lyon is a major French city known for its rich history, gastronomy, and role as a cultural and economic hub in the Auvergne-Rhône-Alpes region.
-
A.
Lyon
chosen
Lyon is a major city in east-central France known for its historical and architectural landmarks, gastronomy, and role as a key economic and cultural center.
-
B.
Lyons
Lyons is a small city in southeastern Georgia, United States, known as the administrative and commercial hub of Toombs County.
-
C.
Lyons
Lyons is a sports team or athletic program associated with Wheaton College, commonly referred to by this shortened name.
-
D.
Clermont-Ferrand
Clermont-Ferrand is a central French city known for its historic cathedral built of black volcanic stone and as the longtime headquarters of the tire company Michelin.
-
E.
Rodez
Rodez is a historic cathedral city in southern France that serves as the capital of the Aveyron department in the Occitanie region.
- F. None of above.
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_69c008f6b5048190a09064116062cf69 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f47d2dc8190ad874be6902d8a4c |
completed | March 22, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11c83f8bc8190bdf139c9da2dd66b |
completed | March 23, 2026, 10:57 a.m. |
| NEDg | Description generation | batch_69c11d9102648190a61e9a85ead0fff4 |
completed | March 23, 2026, 11:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c11e76f5c48190adabb10472729cb2 |
completed | March 23, 2026, 11:05 a.m. |
Created at: March 22, 2026, 3:32 p.m.