Triple
T9171801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Lucca |
E220097
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Barga
Barga is a historic hilltop town in Tuscany, Italy, renowned for its medieval architecture, scenic mountain setting, and strong cultural ties to Scotland.
|
E781593
|
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: Barga | Statement: [Province of Lucca, contains, Barga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barga Context triple: [Province of Lucca, contains, Barga]
-
A.
Ballari
Ballari is a major city in the Indian state of Karnataka, known for its rich mineral resources and historical forts.
-
B.
Rosciano
Rosciano is a small Italian municipality in the Abruzzo region, known for its rural landscape and traditional local agriculture.
-
C.
Gioia del Colle
Gioia del Colle is a historic town in the Apulia region of southern Italy, known for its medieval castle, wine production, and strategic location between Bari and Taranto.
-
D.
Loiano
Loiano is a small Italian town in the Emilia-Romagna region, known for its Apennine hillside setting and astronomical observatory.
-
E.
Schignano
Schignano is a small Italian village in the Lombardy region, known for its traditional Alpine setting and historic Carnival celebrations.
- 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: Barga Triple: [Province of Lucca, contains, Barga]
Generated description
Barga is a historic hilltop town in Tuscany, Italy, renowned for its medieval architecture, scenic mountain setting, and strong cultural ties to Scotland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Barga Target entity description: Barga is a historic hilltop town in Tuscany, Italy, renowned for its medieval architecture, scenic mountain setting, and strong cultural ties to Scotland.
-
A.
Ballari
Ballari is a major city in the Indian state of Karnataka, known for its rich mineral resources and historical forts.
-
B.
Rosciano
Rosciano is a small Italian municipality in the Abruzzo region, known for its rural landscape and traditional local agriculture.
-
C.
Gioia del Colle
Gioia del Colle is a historic town in the Apulia region of southern Italy, known for its medieval castle, wine production, and strategic location between Bari and Taranto.
-
D.
Loiano
Loiano is a small Italian town in the Emilia-Romagna region, known for its Apennine hillside setting and astronomical observatory.
-
E.
Schignano
Schignano is a small Italian village in the Lombardy region, known for its traditional Alpine setting and historic Carnival celebrations.
- 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_69ca83e467108190abcae6a33b3d4dad |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaae38ee48190bf783477bc37913d |
completed | April 1, 2026, 5:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0549d81d88190bea0995ad0016437 |
completed | April 4, 2026, midnight |
| NEDg | Description generation | batch_69d0553c2b58819086a651863f884064 |
completed | April 4, 2026, 12:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0562e41bc8190801c75e962600df2 |
completed | April 4, 2026, 12:07 a.m. |
Created at: March 30, 2026, 7:22 p.m.