Triple
T6908288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langholm |
E159865
|
entity |
| Predicate | hasPostTown |
P2711
|
FINISHED |
| Object |
LANGHOLM
LANGHOLM is a small town in Dumfries and Galloway, Scotland, known historically for its textile industry and scenic location in the Esk Valley.
|
E627885
|
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: LANGHOLM | Statement: [Langholm, hasPostTown, LANGHOLM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LANGHOLM Context triple: [Langholm, hasPostTown, LANGHOLM]
-
A.
Hafslund
Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
-
B.
Molndal
Mölndal is a Swedish city in Västra Götaland County, just south of Gothenburg, known for its industrial heritage and proximity to major research and technology hubs.
-
C.
Katrineholm
Katrineholm is a small Swedish town known as a regional transport hub and service center in central Södermanland.
-
D.
Lodalen
Lodalen is a small valley and residential-industrial area in Oslo, Norway, situated near the inner-city districts and railway facilities.
-
E.
Holmen
Holmen is a residential neighborhood in Oslo, Norway, known for its green surroundings and location within the borough of Vestre Aker.
- 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: LANGHOLM Triple: [Langholm, hasPostTown, LANGHOLM]
Generated description
LANGHOLM is a small town in Dumfries and Galloway, Scotland, known historically for its textile industry and scenic location in the Esk Valley.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: LANGHOLM Target entity description: LANGHOLM is a small town in Dumfries and Galloway, Scotland, known historically for its textile industry and scenic location in the Esk Valley.
-
A.
Hafslund
Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
-
B.
Molndal
Mölndal is a Swedish city in Västra Götaland County, just south of Gothenburg, known for its industrial heritage and proximity to major research and technology hubs.
-
C.
Katrineholm
Katrineholm is a small Swedish town known as a regional transport hub and service center in central Södermanland.
-
D.
Lodalen
Lodalen is a small valley and residential-industrial area in Oslo, Norway, situated near the inner-city districts and railway facilities.
-
E.
Holmen
Holmen is a residential neighborhood in Oslo, Norway, known for its green surroundings and location within the borough of Vestre Aker.
- 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_69c68839ccb88190b4aa5cc1aca3448f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9bd7b3c8190842eb83679c322d5 |
completed | March 27, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c74901aee08190a5e132200fd58c05 |
completed | March 28, 2026, 3:20 a.m. |
| NEDg | Description generation | batch_69c74ab850c4819082cd229796176ff0 |
completed | March 28, 2026, 3:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c74b5d391481909273e62259732ef2 |
completed | March 28, 2026, 3:30 a.m. |
Created at: March 27, 2026, 2:25 p.m.