Triple
T1539814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louisiana |
E32838
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Lafayette
Lafayette is a mid-sized city in southern Louisiana known as a cultural hub of Cajun and Creole music, food, and festivals.
|
E178275
|
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: Lafayette | Statement: [Louisiana, hasMajorCity, Lafayette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lafayette Context triple: [Louisiana, hasMajorCity, Lafayette]
-
A.
Lafayette
Lafayette was a French aristocrat and military officer who became a key general in the American Revolutionary War and a symbol of Franco-American alliance.
-
B.
Vincennes
Vincennes is a historic commune just east of Paris, France, known for its medieval Château de Vincennes and long-standing royal connections.
-
C.
Lafayette, Indiana
Lafayette, Indiana is a mid-sized city in northwestern Indiana known as a regional economic and educational hub near Purdue University.
-
D.
Orleans
Orleans is a coastal town on outer Cape Cod in Massachusetts known for its beaches, fishing, and role as a popular summer vacation destination.
-
E.
Saint-Louis
Saint-Louis is a French border town in the Alsace region, adjacent to Basel and known as a key cross-border transit and commuter hub between France, Switzerland, and Germany.
- 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: Lafayette Triple: [Louisiana, hasMajorCity, Lafayette]
Generated description
Lafayette is a mid-sized city in southern Louisiana known as a cultural hub of Cajun and Creole music, food, and festivals.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lafayette Target entity description: Lafayette is a mid-sized city in southern Louisiana known as a cultural hub of Cajun and Creole music, food, and festivals.
-
A.
Lafayette
Lafayette was a French aristocrat and military officer who became a key general in the American Revolutionary War and a symbol of Franco-American alliance.
-
B.
Vincennes
Vincennes is a historic commune just east of Paris, France, known for its medieval Château de Vincennes and long-standing royal connections.
-
C.
Lafayette, Indiana
Lafayette, Indiana is a mid-sized city in northwestern Indiana known as a regional economic and educational hub near Purdue University.
-
D.
Orleans
Orleans is a coastal town on outer Cape Cod in Massachusetts known for its beaches, fishing, and role as a popular summer vacation destination.
-
E.
Saint-Louis
Saint-Louis is a French border town in the Alsace region, adjacent to Basel and known as a key cross-border transit and commuter hub between France, Switzerland, and Germany.
- 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_69a885ed29088190a3c2d5a3d100c16e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9083c942481909168394b6674d82b |
completed | March 5, 2026, 4:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad4018f4c08190ad1994389b4e244c |
completed | March 8, 2026, 9:23 a.m. |
| NEDg | Description generation | batch_69ad40b363bc819098a6d80f07cc80ce |
completed | March 8, 2026, 9:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad40fee2348190a048e97bfd747267 |
completed | March 8, 2026, 9:27 a.m. |
Created at: March 4, 2026, 7:26 p.m.