Triple
T6845282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Terni |
E157878
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Allerona
Allerona is a small historic hill town in the Umbria region of central Italy, known for its medieval architecture and scenic countryside.
|
E623018
|
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: Allerona | Statement: [Province of Terni, contains, Allerona]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Allerona Context triple: [Province of Terni, contains, Allerona]
-
A.
Atessa
Atessa is a town and municipality in the Abruzzo region of central Italy, known for its industrial activity and automotive manufacturing facilities.
-
B.
Avallon
Avallon is a historic commune in central France known for its medieval architecture and scenic location on a granite outcrop in the Burgundy region.
-
C.
Lelylaan
Lelylaan is a transport hub and railway/metro station in Amsterdam’s Nieuw-West district, connecting metro, train, tram, and bus services.
-
D.
Candalus
Candalus is a figure from Greek mythology known as a son of Rhode.
-
E.
Tarana
Tarana is the first name of Tarana Burke, the American civil rights activist who founded the Me Too movement.
- 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: Allerona Triple: [Province of Terni, contains, Allerona]
Generated description
Allerona is a small historic hill town in the Umbria region of central Italy, known for its medieval architecture and scenic countryside.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Allerona Target entity description: Allerona is a small historic hill town in the Umbria region of central Italy, known for its medieval architecture and scenic countryside.
-
A.
Atessa
Atessa is a town and municipality in the Abruzzo region of central Italy, known for its industrial activity and automotive manufacturing facilities.
-
B.
Avallon
Avallon is a historic commune in central France known for its medieval architecture and scenic location on a granite outcrop in the Burgundy region.
-
C.
Lelylaan
Lelylaan is a transport hub and railway/metro station in Amsterdam’s Nieuw-West district, connecting metro, train, tram, and bus services.
-
D.
Candalus
Candalus is a figure from Greek mythology known as a son of Rhode.
-
E.
Tarana
Tarana is the first name of Tarana Burke, the American civil rights activist who founded the Me Too movement.
- 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_69c6882ed4c081909dc465a7cf8838be |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d7ca96008190ba79563c2a9a9b0e |
completed | March 27, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c72fc42e688190baa8413883e5506c |
completed | March 28, 2026, 1:32 a.m. |
| NEDg | Description generation | batch_69c7304c0bac8190a9ece4e50ab49586 |
completed | March 28, 2026, 1:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7310fa9bc8190bfb0a43890dc5e96 |
completed | March 28, 2026, 1:38 a.m. |
Created at: March 27, 2026, 2:19 p.m.