Triple
T1089915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tagus River |
E24137
|
entity |
| Predicate | passesThroughRegion |
P3448
|
FINISHED |
| Object |
Ribatejo
Ribatejo is a historical province in central Portugal known for its fertile plains, agriculture, and traditional bullfighting culture.
|
E123602
|
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: Ribatejo | Statement: [Tagus River, passesThroughRegion, Ribatejo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ribatejo Context triple: [Tagus River, passesThroughRegion, Ribatejo]
-
A.
Rentería
Rentería (Errenteria) is a town in the Basque province of Gipuzkoa in northern Spain, known for its industrial history and proximity to San Sebastián.
-
B.
Rivas
Rivas is a city in southwestern Nicaragua known as a regional commercial center and gateway between Lake Nicaragua and the Pacific coast.
-
C.
Alvescot
Alvescot is a small rural village in Oxfordshire, England, known for its traditional stone cottages and historic parish church.
-
D.
Logudoro
Logudoro is a historical-cultural region in northern Sardinia known for its distinctive Sardinian dialect, medieval heritage, and rural landscapes.
-
E.
Obarrio
Obarrio is a prominent upscale neighborhood in Panama City known for its concentration of banks, corporate offices, and modern high-rise buildings.
- 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: Ribatejo Triple: [Tagus River, passesThroughRegion, Ribatejo]
Generated description
Ribatejo is a historical province in central Portugal known for its fertile plains, agriculture, and traditional bullfighting culture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ribatejo Target entity description: Ribatejo is a historical province in central Portugal known for its fertile plains, agriculture, and traditional bullfighting culture.
-
A.
Rentería
Rentería (Errenteria) is a town in the Basque province of Gipuzkoa in northern Spain, known for its industrial history and proximity to San Sebastián.
-
B.
Rivas
Rivas is a city in southwestern Nicaragua known as a regional commercial center and gateway between Lake Nicaragua and the Pacific coast.
-
C.
Alvescot
Alvescot is a small rural village in Oxfordshire, England, known for its traditional stone cottages and historic parish church.
-
D.
Logudoro
Logudoro is a historical-cultural region in northern Sardinia known for its distinctive Sardinian dialect, medieval heritage, and rural landscapes.
-
E.
Obarrio
Obarrio is a prominent upscale neighborhood in Panama City known for its concentration of banks, corporate offices, and modern high-rise buildings.
- 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_69a49404428c819092dcc9632f5f7b8b |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b97f216881909e9b8943ce2078e4 |
completed | March 1, 2026, 10:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac42b41618819087884c292db4ed55 |
completed | March 7, 2026, 3:22 p.m. |
| NEDg | Description generation | batch_69ac4336328481908aba0260c6504a1a |
completed | March 7, 2026, 3:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac43b578d48190af1478c9f6c8f712 |
completed | March 7, 2026, 3:26 p.m. |
Created at: March 1, 2026, 7:42 p.m.