Triple
T12287342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gave de Pau basin |
E292863
|
entity |
| Predicate | containsRiver |
P165
|
FINISHED |
| Object |
Gave d’Azun
Gave d’Azun is a mountain river in the French Pyrenees that flows through the Azun Valley before joining the Gave de Pau.
|
E988992
|
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: Gave d’Azun | Statement: [Gave de Pau basin, containsRiver, Gave d’Azun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gave d’Azun Context triple: [Gave de Pau basin, containsRiver, Gave d’Azun]
-
A.
Ozurgeti
Ozurgeti is a city in western Georgia that serves as the administrative and cultural center of the Guria region.
-
B.
Igarra
Igarra is a prominent town in Edo State, Nigeria, known as the traditional headquarters of the Etuno people and the administrative center of the Akoko-Edo Local Government Area.
-
C.
Elorrio
Elorrio is a historic town in northern Spain’s Basque Country, known for its well-preserved medieval center and traditional Basque architecture.
-
D.
Beasain
Beasain is a town in the Basque province of Gipuzkoa in northern Spain, known for its strong industrial base and railway manufacturing heritage.
-
E.
Amurrio
Amurrio is a town and municipality in the Basque province of Álava in northern Spain, known for its industrial activity and scenic rural surroundings.
- 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: Gave d’Azun Triple: [Gave de Pau basin, containsRiver, Gave d’Azun]
Generated description
Gave d’Azun is a mountain river in the French Pyrenees that flows through the Azun Valley before joining the Gave de Pau.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gave d’Azun Target entity description: Gave d’Azun is a mountain river in the French Pyrenees that flows through the Azun Valley before joining the Gave de Pau.
-
A.
Ozurgeti
Ozurgeti is a city in western Georgia that serves as the administrative and cultural center of the Guria region.
-
B.
Igarra
Igarra is a prominent town in Edo State, Nigeria, known as the traditional headquarters of the Etuno people and the administrative center of the Akoko-Edo Local Government Area.
-
C.
Elorrio
Elorrio is a historic town in northern Spain’s Basque Country, known for its well-preserved medieval center and traditional Basque architecture.
-
D.
Beasain
Beasain is a town in the Basque province of Gipuzkoa in northern Spain, known for its strong industrial base and railway manufacturing heritage.
-
E.
Amurrio
Amurrio is a town and municipality in the Basque province of Álava in northern Spain, known for its industrial activity and scenic rural surroundings.
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91d1ffb208190a4b86d7d4ceee045 |
completed | April 10, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6555c73208190a8846a5db1a6802e |
completed | May 2, 2026, 7:49 p.m. |
| NEDg | Description generation | batch_69f6566dccc0819085e059c7b0288f6c |
completed | May 2, 2026, 7:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f657aa1bf48190a884e0dfce31e30e |
completed | May 2, 2026, 7:59 p.m. |
Created at: April 8, 2026, 9:52 p.m.