Triple
T19639405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stadio Luigi Ferraris |
E471489
|
entity |
| Predicate | neighborhood |
P988
|
FINISHED |
| Object |
Marassi
Marassi is a residential district of Genoa, Italy, best known for hosting the historic Stadio Luigi Ferraris football stadium.
|
E1387545
|
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: Marassi | Statement: [Stadio Luigi Ferraris, neighborhood, Marassi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marassi Context triple: [Stadio Luigi Ferraris, neighborhood, Marassi]
-
A.
Martos
Martos is a historic town in southern Spain’s Andalusia region, known for its olive oil production and hilltop setting dominated by a medieval castle.
-
B.
Zefta
Zefta is a village located in southern Lebanon within the Nabatieh Governorate.
-
C.
Akhras
Akhras is a Syrian-origin family name best known for being the maiden surname of Asma al-Assad, the First Lady of Syria.
-
D.
Taris
Taris is a heavily urbanized, stratified ecumenopolis world in the Star Wars universe, best known for its prominent role in the Old Republic era stories and games.
-
E.
Berriane
Berriane is a town in Algeria known as part of the historic M’zab oasis region, characterized by its traditional architecture and Saharan environment.
- 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: Marassi Triple: [Stadio Luigi Ferraris, neighborhood, Marassi]
Generated description
Marassi is a residential district of Genoa, Italy, best known for hosting the historic Stadio Luigi Ferraris football stadium.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marassi Target entity description: Marassi is a residential district of Genoa, Italy, best known for hosting the historic Stadio Luigi Ferraris football stadium.
-
A.
Martos
Martos is a historic town in southern Spain’s Andalusia region, known for its olive oil production and hilltop setting dominated by a medieval castle.
-
B.
Zefta
Zefta is a village located in southern Lebanon within the Nabatieh Governorate.
-
C.
Akhras
Akhras is a Syrian-origin family name best known for being the maiden surname of Asma al-Assad, the First Lady of Syria.
-
D.
Taris
Taris is a heavily urbanized, stratified ecumenopolis world in the Star Wars universe, best known for its prominent role in the Old Republic era stories and games.
-
E.
Berriane
Berriane is a town in Algeria known as part of the historic M’zab oasis region, characterized by its traditional architecture and Saharan environment.
- 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e641215df48190926b38e6502bb83e |
completed | April 20, 2026, 3:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a077ee4e2e08190a3f9faa22402817f |
completed | May 15, 2026, 8:15 p.m. |
| NEDg | Description generation | batch_6a077f74e4fc81909fd1c65af64ba68f |
completed | May 15, 2026, 8:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0780e305f08190805e21212dec0b39 |
completed | May 15, 2026, 8:24 p.m. |
Created at: April 10, 2026, 1:44 p.m.