Triple
T8401495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kidwelly |
E198381
|
entity |
| Predicate | nearbyVillage |
P4647
|
FINISHED |
| Object |
Trimsaran
Trimsaran is a former coal-mining village in Carmarthenshire, Wales, known for its industrial heritage and rural setting.
|
E730735
|
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: Trimsaran | Statement: [Kidwelly, nearbyVillage, Trimsaran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trimsaran Context triple: [Kidwelly, nearbyVillage, Trimsaran]
-
A.
Galeata
Galeata is a small historic town in Italy’s Emilia-Romagna region, known for its Roman and medieval heritage in the Apennine foothills.
-
B.
Miaoulis
Miaoulis is a Greek surname most famously associated with Admiral Andreas Miaoulis, a key naval leader in the Greek War of Independence.
-
C.
Taganga
Taganga is a small fishing village and popular backpacker destination on Colombia’s Caribbean coast, known for its beaches, diving, and proximity to Tayrona National Natural Park.
-
D.
Navadvip
Navadvip is a historic town in West Bengal, India, renowned as a major center of Gaudiya Vaishnavism and the birthplace of the saint Chaitanya Mahaprabhu.
-
E.
Lisberg
Lisberg is a Danish-origin surname most notably associated with figures such as Jens Oliver Lisberg.
- 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: Trimsaran Triple: [Kidwelly, nearbyVillage, Trimsaran]
Generated description
Trimsaran is a former coal-mining village in Carmarthenshire, Wales, known for its industrial heritage and rural setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Trimsaran Target entity description: Trimsaran is a former coal-mining village in Carmarthenshire, Wales, known for its industrial heritage and rural setting.
-
A.
Galeata
Galeata is a small historic town in Italy’s Emilia-Romagna region, known for its Roman and medieval heritage in the Apennine foothills.
-
B.
Miaoulis
Miaoulis is a Greek surname most famously associated with Admiral Andreas Miaoulis, a key naval leader in the Greek War of Independence.
-
C.
Taganga
Taganga is a small fishing village and popular backpacker destination on Colombia’s Caribbean coast, known for its beaches, diving, and proximity to Tayrona National Natural Park.
-
D.
Navadvip
Navadvip is a historic town in West Bengal, India, renowned as a major center of Gaudiya Vaishnavism and the birthplace of the saint Chaitanya Mahaprabhu.
-
E.
Lisberg
Lisberg is a Danish-origin surname most notably associated with figures such as Jens Oliver Lisberg.
- 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_69ca8310df9c8190b25f16161cca3e41 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb824da3148190bfa3a1abfdfa02de |
completed | March 31, 2026, 8:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde8789a608190a3503f544a19d204 |
completed | April 2, 2026, 3:54 a.m. |
| NEDg | Description generation | batch_69cdebfd60188190a1681344e2bf1e9e |
completed | April 2, 2026, 4:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cded2fa42c8190bfbfc79caf38bf8e |
completed | April 2, 2026, 4:14 a.m. |
Created at: March 30, 2026, 6:04 p.m.