Triple
T4890403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toombs County |
E109544
|
entity |
| Predicate | countySeat |
P383
|
FINISHED |
| Object |
Lyons
Lyons is a small city in southeastern Georgia, United States, known as the administrative and commercial hub of Toombs County.
|
E527592
|
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: Lyons | Statement: [Toombs County, countySeat, Lyons]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lyons Context triple: [Toombs County, countySeat, Lyons]
-
A.
Lyons
Lyons is a sports team or athletic program associated with Wheaton College, commonly referred to by this shortened name.
-
B.
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.
-
C.
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.
-
D.
Rodez
Rodez is a historic cathedral city in southern France that serves as the capital of the Aveyron department in the Occitanie region.
-
E.
Grenoble
Grenoble is a major city in southeastern France, known for its Alpine setting, universities, and research centers.
- 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: Lyons Triple: [Toombs County, countySeat, Lyons]
Generated description
Lyons is a small city in southeastern Georgia, United States, known as the administrative and commercial hub of Toombs County.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lyons Target entity description: Lyons is a small city in southeastern Georgia, United States, known as the administrative and commercial hub of Toombs County.
-
A.
Lyons
Lyons is a sports team or athletic program associated with Wheaton College, commonly referred to by this shortened name.
-
B.
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.
-
C.
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.
-
D.
Rodez
Rodez is a historic cathedral city in southern France that serves as the capital of the Aveyron department in the Occitanie region.
-
E.
Grenoble
Grenoble is a major city in southeastern France, known for its Alpine setting, universities, and research centers.
- 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_69bd440f71348190b99938e59fb7f9a1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e07ca10819083f80f12374544b1 |
completed | March 20, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bff2a7e5b081909d3d64fc62c48eb3 |
completed | March 22, 2026, 1:46 p.m. |
| NEDg | Description generation | batch_69bff357b39c8190824415483c4ec843 |
completed | March 22, 2026, 1:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bff3ad10b88190b9ef4fff5642ecc4 |
completed | March 22, 2026, 1:50 p.m. |
Created at: March 20, 2026, 1:28 p.m.