Triple
T10865670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tynedale |
E256522
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Greenhead |
E766704
|
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: Greenhead | Statement: [Tynedale, contains, Greenhead]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greenhead Context triple: [Tynedale, contains, Greenhead]
-
A.
Greenhead
chosen
Greenhead is a small village in Northumberland, England, known for its proximity to Hadrian’s Wall and scenic rural surroundings.
-
B.
Goose Green
Goose Green is a settlement on East Falkland in the Falkland Islands, best known as the site of a major land battle during the 1982 Falklands War.
-
C.
Goose Green
Goose Green is a small public park and open green space in the East Dulwich area of south London, popular for recreation and community events.
-
D.
Greenleaf
Greenleaf is a dramatic television series that explores the secrets, scandals, and power struggles within a wealthy African-American megachurch family.
-
E.
Greenleaf
Greenleaf is the middle name of the 19th-century American Quaker poet and abolitionist John Greenleaf Whittier.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7516cebe881909ed358a7641f6a12 |
completed | April 9, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7d7b32081909dd5f8ae3fe293be |
completed | April 15, 2026, 8:40 p.m. |
Created at: April 8, 2026, 9:20 p.m.