Triple
T10594510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Venoge |
E250074
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object |
La Senoge
La Senoge is a small river in the canton of Vaud, Switzerland, that flows through the Jura region before joining the larger La Venoge.
|
E873463
|
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: La Senoge | Statement: [La Venoge, hasTributary, La Senoge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Senoge Context triple: [La Venoge, hasTributary, La Senoge]
-
A.
Nisaea
Nisaea was the port town and harbor of ancient Megara in Greece, serving as its main maritime outlet on the Saronic Gulf.
-
B.
Esla
The Esla is a major river in northwestern Spain that flows through the provinces of León and Zamora before joining the Duero.
-
C.
Algés
Algés is a coastal civil parish in the municipality of Oeiras, just west of central Lisbon, Portugal, known for its riverside location along the Tagus and proximity to the Belém district.
-
D.
Bucasia
Bucasia is a coastal suburb in Queensland, Australia, known for its long sandy beach and residential community within the Mackay Region.
-
E.
Moura
Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
- 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: La Senoge Triple: [La Venoge, hasTributary, La Senoge]
Generated description
La Senoge is a small river in the canton of Vaud, Switzerland, that flows through the Jura region before joining the larger La Venoge.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: La Senoge Target entity description: La Senoge is a small river in the canton of Vaud, Switzerland, that flows through the Jura region before joining the larger La Venoge.
-
A.
Nisaea
Nisaea was the port town and harbor of ancient Megara in Greece, serving as its main maritime outlet on the Saronic Gulf.
-
B.
Esla
The Esla is a major river in northwestern Spain that flows through the provinces of León and Zamora before joining the Duero.
-
C.
Algés
Algés is a coastal civil parish in the municipality of Oeiras, just west of central Lisbon, Portugal, known for its riverside location along the Tagus and proximity to the Belém district.
-
D.
Bucasia
Bucasia is a coastal suburb in Queensland, Australia, known for its long sandy beach and residential community within the Mackay Region.
-
E.
Moura
Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5278bacd88190a50dedfa59b622fc |
completed | April 7, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95e8de2e88190835954abb2ac2ece |
completed | April 10, 2026, 8:33 p.m. |
| NEDg | Description generation | batch_69d95f80d0c48190b88e3a4b3e42279c |
completed | April 10, 2026, 8:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d9602a1d688190ad0f3014d69049cc |
completed | April 10, 2026, 8:40 p.m. |
Created at: April 6, 2026, 12:41 p.m.