Triple
T13345453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Segrià |
E317936
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Seròs
Seròs is a municipality in the comarca of Segrià in Catalonia, northeastern Spain, known for its agricultural landscape along the Segre River.
|
E1035660
|
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: Seròs | Statement: [Segrià, hasMunicipality, Seròs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seròs Context triple: [Segrià, hasMunicipality, Seròs]
-
A.
Serua
Serua is a small volcanic island in Indonesia’s Banda Sea, known for its steep terrain, active geology, and remote location within the Banda Arc.
-
B.
Súr
Súr was a Hungarian military leader who served as one of the commanders of the Magyar forces defeated by Otto I at the Battle of Lechfeld in 955.
-
C.
Soroa
Soroa is a small Cuban village and popular ecotourism destination known for its lush mountain scenery, waterfalls, and orchid garden.
-
D.
Sekyra
Sekyra is a notable novel by Czech writer Ludvík Vaculík, recognized for its critical portrayal of life under the communist regime in Czechoslovakia.
-
E.
Sierroz
Sierroz is a river in eastern France that serves as one of the tributaries feeding into Lac du Bourget.
- 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: Seròs Triple: [Segrià, hasMunicipality, Seròs]
Generated description
Seròs is a municipality in the comarca of Segrià in Catalonia, northeastern Spain, known for its agricultural landscape along the Segre River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Seròs Target entity description: Seròs is a municipality in the comarca of Segrià in Catalonia, northeastern Spain, known for its agricultural landscape along the Segre River.
-
A.
Serua
Serua is a small volcanic island in Indonesia’s Banda Sea, known for its steep terrain, active geology, and remote location within the Banda Arc.
-
B.
Súr
Súr was a Hungarian military leader who served as one of the commanders of the Magyar forces defeated by Otto I at the Battle of Lechfeld in 955.
-
C.
Soroa
Soroa is a small Cuban village and popular ecotourism destination known for its lush mountain scenery, waterfalls, and orchid garden.
-
D.
Sekyra
Sekyra is a notable novel by Czech writer Ludvík Vaculík, recognized for its critical portrayal of life under the communist regime in Czechoslovakia.
-
E.
Sierroz
Sierroz is a river in eastern France that serves as one of the tributaries feeding into Lac du Bourget.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e89c65c819093f3bea11d6073c5 |
completed | April 11, 2026, 1:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f439b3c8190b35fd4d097d65068 |
completed | May 3, 2026, 10:11 a.m. |
| NEDg | Description generation | batch_69f7204ac36c8190a04e921442489e9c |
completed | May 3, 2026, 10:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7221887208190ac98945a023bc496 |
completed | May 3, 2026, 10:23 a.m. |
Created at: April 9, 2026, 9:31 p.m.