Triple
T4439834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adige |
E95742
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object |
Talvera
Talvera is a river in northern Italy that flows through South Tyrol and joins the Adige near the city of Bolzano.
|
E445282
|
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: Talvera | Statement: [Adige, hasTributary, Talvera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Talvera Context triple: [Adige, hasTributary, Talvera]
-
A.
Trévélez
Trévélez is a small Spanish mountain village in the Alpujarras region of Granada, renowned for being one of the highest villages in Spain and for its traditional air-cured ham (jamón).
-
B.
Caseres
Caseres is a small rural municipality located in the Terra Alta comarca of Catalonia, Spain, known for its agricultural landscape and traditional village character.
-
C.
Astorga
Astorga is a historic city in the province of León, Spain, known for its Roman heritage, medieval cathedral, and a Modernist Episcopal Palace designed by Antoni Gaudí.
-
D.
Alcanena
Alcanena is a Portuguese municipality known for its traditional leather and tanning industry, located in the Centro Region of Portugal.
-
E.
San Javier
San Javier is a Chilean town known for its agricultural activity and wine production in the Maule Region.
- 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: Talvera Triple: [Adige, hasTributary, Talvera]
Generated description
Talvera is a river in northern Italy that flows through South Tyrol and joins the Adige near the city of Bolzano.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Talvera Target entity description: Talvera is a river in northern Italy that flows through South Tyrol and joins the Adige near the city of Bolzano.
-
A.
Trévélez
Trévélez is a small Spanish mountain village in the Alpujarras region of Granada, renowned for being one of the highest villages in Spain and for its traditional air-cured ham (jamón).
-
B.
Caseres
Caseres is a small rural municipality located in the Terra Alta comarca of Catalonia, Spain, known for its agricultural landscape and traditional village character.
-
C.
Astorga
Astorga is a historic city in the province of León, Spain, known for its Roman heritage, medieval cathedral, and a Modernist Episcopal Palace designed by Antoni Gaudí.
-
D.
Alcanena
Alcanena is a Portuguese municipality known for its traditional leather and tanning industry, located in the Centro Region of Portugal.
-
E.
San Javier
San Javier is a Chilean town known for its agricultural activity and wine production in the Maule Region.
- 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_69b3453ea2b48190a26f154b3b8fece5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355aaa9288190b95d875d343d6ee5 |
completed | March 13, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b67baa14648190811970a45dd0d185 |
completed | March 15, 2026, 9:28 a.m. |
| NEDg | Description generation | batch_69b67ffd42908190b6b0b79d12266fa6 |
completed | March 15, 2026, 9:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b680db60ec81909a58427ab7be15d7 |
completed | March 15, 2026, 9:50 a.m. |
Created at: March 12, 2026, 11:31 p.m.