Triple
T11502522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Lugg |
E272697
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Hereford |
E65056
|
NE FINISHED |
How this triple was built (2 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: Hereford | Statement: [River Lugg, flowsThrough, Hereford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hereford Context triple: [River Lugg, flowsThrough, Hereford]
-
A.
Hereford
chosen
Hereford is a cathedral city in Herefordshire, England, known for its historic architecture and role as a military and agricultural center.
-
B.
Hereford
Hereford is a small city in the Texas Panhandle known for its strong agricultural and cattle industry.
-
C.
Wellington, Shropshire
Wellington, Shropshire is a historic market town in Shropshire, England, now part of the new town of Telford.
-
D.
Swindon
Swindon is a large town in Wiltshire, England, known as a major commercial and commuter hub in the southwest with strong railway and industrial heritage.
-
E.
Frampton-on-Severn
Frampton-on-Severn is a picturesque village in Gloucestershire, England, known for its large village green and historic Cotswold stone buildings.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d85de55cbc8190be71c2d03dc044f2 |
completed | April 10, 2026, 2:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e624d666c081908253cea4e2da1a4a |
completed | April 20, 2026, 1:06 p.m. |
Created at: April 8, 2026, 9:36 p.m.