Triple
T2720367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State of São Paulo |
E60066
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Franca
Franca is a city in the northeastern part of the Brazilian state of São Paulo, known historically for its leather and footwear industry.
|
E293506
|
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: Franca | Statement: [State of São Paulo, hasCity, Franca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Franca Context triple: [State of São Paulo, hasCity, Franca]
-
A.
Włochy
Włochy is a district in the southwestern part of Warsaw, Poland, known for its mix of residential areas, industrial zones, and major transport infrastructure including the city’s main airport.
-
B.
Senigallia
Senigallia is a historic coastal town in Italy’s Marche region, known for its Adriatic seaside resort, Renaissance heritage, and well-preserved old town.
-
C.
France and Italy
France and Italy are neighboring European countries that share a long Alpine border, rich cultural heritage, and significant historical, economic, and touristic ties.
-
D.
Italo
Italo is a masculine Italian given name historically borne by notable figures in politics, aviation, literature, and the arts.
-
E.
Belonia
Belonia is a small town in the South Tripura district of the Indian state of Tripura, near the India–Bangladesh border.
- 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: Franca Triple: [State of São Paulo, hasCity, Franca]
Generated description
Franca is a city in the northeastern part of the Brazilian state of São Paulo, known historically for its leather and footwear industry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Franca Target entity description: Franca is a city in the northeastern part of the Brazilian state of São Paulo, known historically for its leather and footwear industry.
-
A.
Włochy
Włochy is a district in the southwestern part of Warsaw, Poland, known for its mix of residential areas, industrial zones, and major transport infrastructure including the city’s main airport.
-
B.
Senigallia
Senigallia is a historic coastal town in Italy’s Marche region, known for its Adriatic seaside resort, Renaissance heritage, and well-preserved old town.
-
C.
France and Italy
France and Italy are neighboring European countries that share a long Alpine border, rich cultural heritage, and significant historical, economic, and touristic ties.
-
D.
Italo
Italo is a masculine Italian given name historically borne by notable figures in politics, aviation, literature, and the arts.
-
E.
Belonia
Belonia is a small town in the South Tripura district of the Indian state of Tripura, near the India–Bangladesh border.
- 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_69ab4b746d248190958e052045c09255 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdab06d388190acf690787fe58ab5 |
completed | March 7, 2026, 7:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afb6914f70819099482893d026f34b |
completed | March 10, 2026, 6:13 a.m. |
| NEDg | Description generation | batch_69afb726182081909570e4cb7a364e4d |
completed | March 10, 2026, 6:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afb78f9d08819087d6f31fe1e4e61c |
completed | March 10, 2026, 6:17 a.m. |
Created at: March 6, 2026, 9:55 p.m.