Triple
T5145468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Perugia |
E116058
|
entity |
| Predicate | containsAdministrativeTerritorialEntity |
P747
|
FINISHED |
| Object |
Preci
Preci is a small historic village and comune in the Umbria region of central Italy, known for its medieval architecture and scenic Apennine mountain setting.
|
E497699
|
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: Preci | Statement: [Province of Perugia, containsAdministrativeTerritorialEntity, Preci]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Preci Context triple: [Province of Perugia, containsAdministrativeTerritorialEntity, Preci]
-
A.
Pris
Pris is a diminutive form of the given name Priscilla, often used as a familiar or affectionate nickname.
-
B.
Pijin
Pijin is an English-based creole language widely used as a lingua franca in the Solomon Islands.
-
C.
Preki
Preki is a former Yugoslav-American professional soccer player and coach best known for his standout MLS career and successful transition into coaching.
-
D.
Pearic
Pearic is a small branch of Austroasiatic languages spoken by indigenous Pearic peoples in parts of Cambodia and Thailand.
-
E.
Pesa
Pesa is a Polish manufacturer of rail vehicles, particularly known for producing modern trams and trains used in various European cities.
- 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: Preci Triple: [Province of Perugia, containsAdministrativeTerritorialEntity, Preci]
Generated description
Preci is a small historic village and comune in the Umbria region of central Italy, known for its medieval architecture and scenic Apennine mountain setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Preci Target entity description: Preci is a small historic village and comune in the Umbria region of central Italy, known for its medieval architecture and scenic Apennine mountain setting.
-
A.
Pris
Pris is a diminutive form of the given name Priscilla, often used as a familiar or affectionate nickname.
-
B.
Pijin
Pijin is an English-based creole language widely used as a lingua franca in the Solomon Islands.
-
C.
Preki
Preki is a former Yugoslav-American professional soccer player and coach best known for his standout MLS career and successful transition into coaching.
-
D.
Pearic
Pearic is a small branch of Austroasiatic languages spoken by indigenous Pearic peoples in parts of Cambodia and Thailand.
-
E.
Pesa
Pesa is a Polish manufacturer of rail vehicles, particularly known for producing modern trams and trains used in various European cities.
- 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_69bd4446c0e08190a7c29dc74976bf03 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd78ac677881909ce8632f1a8af880 |
completed | March 20, 2026, 4:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69becff590ec81908ed03474f21a95f5 |
completed | March 21, 2026, 5:05 p.m. |
| NEDg | Description generation | batch_69bed254037c8190b1487b12425f8abe |
completed | March 21, 2026, 5:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bed2be57108190bc3e758c34ffc34f |
completed | March 21, 2026, 5:17 p.m. |
Created at: March 20, 2026, 1:43 p.m.