Triple
T15568150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ansião |
E374168
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object |
Soure
Soure is a municipality in Portugal’s Coimbra District, known for its rural landscapes, historical heritage, and location in the central region of the country.
|
E374184
|
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: Soure | Statement: [Ansião, borders, Soure]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Soure Context triple: [Ansião, borders, Soure]
-
A.
Sulien
Sulien is a Welsh saint traditionally venerated as a local holy figure associated with churches in Wales.
-
B.
Suvar
Suvar was an important medieval town and trading center in Volga Bulgaria, serving as one of the region’s key political and economic hubs.
-
C.
Suen
Suen is the Sumerian moon god, later known as Sin in Akkadian mythology, associated with the lunar cycle, wisdom, and divination.
-
D.
Sõru
Sõru is a small port village on the southern coast of Hiiumaa Island in Estonia, known for its ferry connection to the mainland and maritime setting.
-
E.
Sosanya
Sosanya is a surname most notably associated with British actress Nina Sosanya, known for her extensive work in television, film, and theatre.
- 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: Soure Triple: [Ansião, borders, Soure]
Generated description
Soure is a municipality in Portugal’s Coimbra District, known for its rural landscapes, historical heritage, and location in the central region of the country.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Soure Target entity description: Soure is a municipality in Portugal’s Coimbra District, known for its rural landscapes, historical heritage, and location in the central region of the country.
-
A.
Soure
chosen
Soure is a Portuguese municipality located in the central region within the Coimbra District, known for its rural landscapes and historical heritage.
-
B.
Sulien
Sulien is a Welsh saint traditionally venerated as a local holy figure associated with churches in Wales.
-
C.
Suvar
Suvar was an important medieval town and trading center in Volga Bulgaria, serving as one of the region’s key political and economic hubs.
-
D.
Suen
Suen is the Sumerian moon god, later known as Sin in Akkadian mythology, associated with the lunar cycle, wisdom, and divination.
-
E.
Sõru
Sõru is a small port village on the southern coast of Hiiumaa Island in Estonia, known for its ferry connection to the mainland and maritime setting.
- F. None of above.
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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04dde90b081908284d9258d4462e3 |
completed | April 16, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c4219a081909acca9f783ecd44b |
completed | May 9, 2026, 3:01 p.m. |
| NEDg | Description generation | batch_69ff50d54960819089491ccb580784b8 |
completed | May 9, 2026, 3:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff5208e9a08190b4a6f4157cf3c237 |
completed | May 9, 2026, 3:26 p.m. |
Created at: April 10, 2026, 4:10 a.m.