Triple
T13710099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Fermo |
E328747
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Massa Fermana
Massa Fermana is a small municipality in Italy’s Marche region, known for its historic hilltop setting and traditional rural character.
|
E1056457
|
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: Massa Fermana | Statement: [Province of Fermo, contains, Massa Fermana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Massa Fermana Context triple: [Province of Fermo, contains, Massa Fermana]
-
A.
Massa Lombarda
Massa Lombarda is a small Italian town in the Emilia-Romagna region, known for its agricultural traditions and location within the fertile Po Valley.
-
B.
Sette
Sette is an Italian weekly news and culture magazine published as a supplement to the national newspaper Corriere della Sera.
-
C.
Monti
Monti is a small town in the Gallura region of northeastern Sardinia, Italy, known for its wine production and rural landscapes.
-
D.
Seravezza
Seravezza is a historic Tuscan town in central Italy, known for its marble quarries and scenic location in the Apuan Alps.
-
E.
Terrasini
Terrasini is a coastal town in the Metropolitan City of Palermo in Sicily, Italy, known for its beaches, fishing traditions, and proximity to Palermo’s airport.
- 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: Massa Fermana Triple: [Province of Fermo, contains, Massa Fermana]
Generated description
Massa Fermana is a small municipality in Italy’s Marche region, known for its historic hilltop setting and traditional rural character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Massa Fermana Target entity description: Massa Fermana is a small municipality in Italy’s Marche region, known for its historic hilltop setting and traditional rural character.
-
A.
Massa Lombarda
Massa Lombarda is a small Italian town in the Emilia-Romagna region, known for its agricultural traditions and location within the fertile Po Valley.
-
B.
Sette
Sette is an Italian weekly news and culture magazine published as a supplement to the national newspaper Corriere della Sera.
-
C.
Monti
Monti is a small town in the Gallura region of northeastern Sardinia, Italy, known for its wine production and rural landscapes.
-
D.
Seravezza
Seravezza is a historic Tuscan town in central Italy, known for its marble quarries and scenic location in the Apuan Alps.
-
E.
Terrasini
Terrasini is a coastal town in the Metropolitan City of Palermo in Sicily, Italy, known for its beaches, fishing traditions, and proximity to Palermo’s airport.
- 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_69d80770b9bc81909f70c8c317d53cff |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dd43949e6c8190ae5e4fa119cde33a |
completed | April 13, 2026, 7:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d52b3708190ae0945e65b271556 |
completed | May 3, 2026, 7:09 p.m. |
| NEDg | Description generation | batch_69f79df2984c8190bed380102ade0725 |
completed | May 3, 2026, 7:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f79e7d50a88190b2a90094dd6d48ad |
completed | May 3, 2026, 7:14 p.m. |
Created at: April 9, 2026, 9:54 p.m.