Triple
T19835219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montgomery Castle |
E476571
|
entity |
| Predicate | replaced |
P101
|
FINISHED |
| Object |
Hen Domen
Hen Domen is the site of an early medieval motte-and-bailey fortification near Montgomery in Powys, Wales, that preceded the later stone Montgomery Castle.
|
E1397635
|
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: Hen Domen | Statement: [Montgomery Castle, replaced, Hen Domen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hen Domen Context triple: [Montgomery Castle, replaced, Hen Domen]
-
A.
Oda Haweis
Oda Haweis was the daughter of modernist poet and artist Mina Loy.
-
B.
Muurame
Muurame is a small municipality in Central Finland known for its scenic lake landscapes and proximity to the city of Jyväskylä.
-
C.
Gotemba
Gotemba is a Japanese city in Shizuoka Prefecture known as a gateway to Mount Fuji and a popular base for outdoor activities and outlet shopping.
-
D.
Toramana
Toramana was a prominent Huna ruler in early 6th-century northern India, known for his extensive military campaigns and significant role in weakening the Gupta Empire.
-
E.
Oda
Oda is a town located in the Eastern Region of Ghana, known for its role as a local commercial and administrative center.
- 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: Hen Domen Triple: [Montgomery Castle, replaced, Hen Domen]
Generated description
Hen Domen is the site of an early medieval motte-and-bailey fortification near Montgomery in Powys, Wales, that preceded the later stone Montgomery Castle.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hen Domen Target entity description: Hen Domen is the site of an early medieval motte-and-bailey fortification near Montgomery in Powys, Wales, that preceded the later stone Montgomery Castle.
-
A.
Oda Haweis
Oda Haweis was the daughter of modernist poet and artist Mina Loy.
-
B.
Muurame
Muurame is a small municipality in Central Finland known for its scenic lake landscapes and proximity to the city of Jyväskylä.
-
C.
Gotemba
Gotemba is a Japanese city in Shizuoka Prefecture known as a gateway to Mount Fuji and a popular base for outdoor activities and outlet shopping.
-
D.
Toramana
Toramana was a prominent Huna ruler in early 6th-century northern India, known for his extensive military campaigns and significant role in weakening the Gupta Empire.
-
E.
Oda
Oda is a town located in the Eastern Region of Ghana, known for its role as a local commercial and administrative center.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656d0e738819093000d3307962328 |
completed | April 20, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07ccd9b71c81909002a92d0e826510 |
completed | May 16, 2026, 1:48 a.m. |
| NEDg | Description generation | batch_6a07cfa7121881908e3256a035f0fffb |
completed | May 16, 2026, 2 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07d0aacc1481908f9b4d96ce34d88b |
completed | May 16, 2026, 2:04 a.m. |
Created at: April 10, 2026, 1:50 p.m.