Triple
T8838300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Třinec |
E210322
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Tavagnacco
Tavagnacco is a municipality in the Friuli-Venezia Giulia region of northeastern Italy, near Udine.
|
E802764
|
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: Tavagnacco | Statement: [Třinec, hasTwinTown, Tavagnacco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tavagnacco Context triple: [Třinec, hasTwinTown, Tavagnacco]
-
A.
Caldogno
Caldogno is a small town in the Veneto region of northern Italy, best known as the birthplace of legendary footballer Roberto Baggio.
-
B.
Bussolengo
Bussolengo is a town and comune in the Veneto region of northern Italy, situated near Verona and known for its agricultural activities and proximity to Lake Garda.
-
C.
Arzignano
Arzignano is an Italian town in the Veneto region known for its leather tanning industry and manufacturing activities.
-
D.
Calolziocorte
Calolziocorte is a town and municipality in the Lombardy region of northern Italy, situated near Lake Como and the Adda River.
-
E.
Bevagna
Bevagna is a historic medieval town in central Italy’s Umbria region, known for its well-preserved Roman and medieval architecture and traditional festivals.
- 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: Tavagnacco Triple: [Třinec, hasTwinTown, Tavagnacco]
Generated description
Tavagnacco is a municipality in the Friuli-Venezia Giulia region of northeastern Italy, near Udine.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tavagnacco Target entity description: Tavagnacco is a municipality in the Friuli-Venezia Giulia region of northeastern Italy, near Udine.
-
A.
Caldogno
Caldogno is a small town in the Veneto region of northern Italy, best known as the birthplace of legendary footballer Roberto Baggio.
-
B.
Bussolengo
Bussolengo is a town and comune in the Veneto region of northern Italy, situated near Verona and known for its agricultural activities and proximity to Lake Garda.
-
C.
Arzignano
Arzignano is an Italian town in the Veneto region known for its leather tanning industry and manufacturing activities.
-
D.
Calolziocorte
Calolziocorte is a town and municipality in the Lombardy region of northern Italy, situated near Lake Como and the Adda River.
-
E.
Bevagna
Bevagna is a historic medieval town in central Italy’s Umbria region, known for its well-preserved Roman and medieval architecture and traditional festivals.
- 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_69ca8388549c819095fd94eadefbb007 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc606c60ac8190b2b6bd7f042c02f8 |
completed | April 1, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d12cb799d0819093256f96df60b16b |
completed | April 4, 2026, 3:22 p.m. |
| NEDg | Description generation | batch_69d1309960c08190aaf1a362cdb47a77 |
completed | April 4, 2026, 3:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d131024f488190b1cf670f5ddf3637 |
completed | April 4, 2026, 3:40 p.m. |
Created at: March 30, 2026, 6:48 p.m.