Triple
T3119079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Calder (Lancashire) |
E65135
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object |
Read
Read is a village in Lancashire, England, situated near the River Calder and known for its residential community and local amenities.
|
E329799
|
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: Read | Statement: [River Calder (Lancashire), flowsThrough, Read]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Read Context triple: [River Calder (Lancashire), flowsThrough, Read]
-
A.
Read
Read is a surname shared by various notable individuals across fields such as politics, arts, and academia.
-
B.
Reading
Reading is a historic city in southeastern Pennsylvania known for its industrial heritage, transportation links, and role as a regional cultural and economic center.
-
C.
Reading
Reading is a major town in Berkshire, England, known as a key commercial and transport hub in the Thames Valley.
-
D.
Reading
"Reading" is an Impressionist painting by Berthe Morisot that depicts a quiet, intimate moment of a woman absorbed in a book.
-
E.
The Reading
The Reading is a Neo-Impressionist painting by Belgian artist Théo van Rysselberghe, depicting figures absorbed in quiet literary contemplation through his characteristic pointillist technique.
- 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: Read Triple: [River Calder (Lancashire), flowsThrough, Read]
Generated description
Read is a village in Lancashire, England, situated near the River Calder and known for its residential community and local amenities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Read Target entity description: Read is a village in Lancashire, England, situated near the River Calder and known for its residential community and local amenities.
-
A.
Read
Read is a surname shared by various notable individuals across fields such as politics, arts, and academia.
-
B.
Reading
Reading is a historic city in southeastern Pennsylvania known for its industrial heritage, transportation links, and role as a regional cultural and economic center.
-
C.
Reading
Reading is a major town in Berkshire, England, known as a key commercial and transport hub in the Thames Valley.
-
D.
Reading
"Reading" is an Impressionist painting by Berthe Morisot that depicts a quiet, intimate moment of a woman absorbed in a book.
-
E.
The Reading
The Reading is a Neo-Impressionist painting by Belgian artist Théo van Rysselberghe, depicting figures absorbed in quiet literary contemplation through his characteristic pointillist technique.
- 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_69ad857fcc088190b0c4d45a5cde6f61 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada4e975f08190a91a01f37a31b766 |
completed | March 8, 2026, 4:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f63f8f881909348d4c6eb3c7e20 |
completed | March 12, 2026, 12:57 a.m. |
| NEDg | Description generation | batch_69b2138e2bdc8190aa0a8a1dcd1e20fc |
completed | March 12, 2026, 1:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b21438b6e881908da0117ebc9bb2b4 |
completed | March 12, 2026, 1:17 a.m. |
Created at: March 8, 2026, 3:04 p.m.