Triple
T12756168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Piacenza |
E304864
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Alseno
Alseno is a small municipality in northern Italy’s Emilia-Romagna region, known for its agricultural landscape and historic rural character.
|
E1001831
|
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: Alseno | Statement: [Province of Piacenza, contains, Alseno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alseno Context triple: [Province of Piacenza, contains, Alseno]
-
A.
Acesines
Acesines is the ancient Greek name for the Chenab River, a major river of the Punjab region in South Asia.
-
B.
Navarcles
Navarcles is a municipality in the comarca of Bages in Catalonia, Spain, known for its location near the Llobregat and Calders rivers.
-
C.
Osuna
Osuna is a historic town in the province of Seville, Spain, known for its rich archaeological heritage, including notable ancient reliefs and other Roman-era remains.
-
D.
Arganzuela
Arganzuela is a central district of Madrid, Spain, known for its extensive redevelopment along the Manzanares River and its mix of residential areas, cultural venues, and green spaces.
-
E.
Illueca
Illueca is a small town in the province of Zaragoza, Aragon, Spain, known historically as the birthplace of Pope Benedict XIII (Pedro de Luna).
- 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: Alseno Triple: [Province of Piacenza, contains, Alseno]
Generated description
Alseno is a small municipality in northern Italy’s Emilia-Romagna region, known for its agricultural landscape and historic rural character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alseno Target entity description: Alseno is a small municipality in northern Italy’s Emilia-Romagna region, known for its agricultural landscape and historic rural character.
-
A.
Acesines
Acesines is the ancient Greek name for the Chenab River, a major river of the Punjab region in South Asia.
-
B.
Navarcles
Navarcles is a municipality in the comarca of Bages in Catalonia, Spain, known for its location near the Llobregat and Calders rivers.
-
C.
Osuna
Osuna is a historic town in the province of Seville, Spain, known for its rich archaeological heritage, including notable ancient reliefs and other Roman-era remains.
-
D.
Arganzuela
Arganzuela is a central district of Madrid, Spain, known for its extensive redevelopment along the Manzanares River and its mix of residential areas, cultural venues, and green spaces.
-
E.
Illueca
Illueca is a small town in the province of Zaragoza, Aragon, Spain, known historically as the birthplace of Pope Benedict XIII (Pedro de Luna).
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d8b57b88190b29b8fdca415c81c |
completed | April 10, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f684f08fac8190b8c480619696bcd1 |
completed | May 2, 2026, 11:12 p.m. |
| NEDg | Description generation | batch_69f6863fada48190afe2ff7896a60094 |
completed | May 2, 2026, 11:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f686bcac94819088782273effbb06a |
completed | May 2, 2026, 11:20 p.m. |
Created at: April 9, 2026, 5:27 p.m.