Triple
T11883514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Douglas Water |
E282714
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object | Douglas |
E282715
|
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: Douglas | Statement: [Douglas Water, hasNearbySettlement, Douglas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Douglas Context triple: [Douglas Water, hasNearbySettlement, Douglas]
-
A.
Douglas
Douglas is a masculine given name of Scottish origin that has been widely used in English-speaking countries.
-
B.
Douglas
Douglas is a narrow-gauge steam locomotive that operates on the historic Talyllyn Railway in Wales.
-
C.
Douglas
chosen
Douglas is a town in South Lanarkshire, Scotland, historically known for its association with the powerful Douglas family and its medieval castle.
-
D.
Douglas
Douglas is a small rural community located within the township of Bonnechere Valley in eastern Ontario, Canada.
-
E.
Douglas
Douglas is a community area on the South Side of Chicago, Illinois, known for its historic residential neighborhoods and proximity to the city’s lakefront.
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d3a02ad4819090faef0e0be732ee |
completed | April 10, 2026, 10:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f281f488a8819082f40dfdd12f29a2 |
completed | April 29, 2026, 10:11 p.m. |
Created at: April 8, 2026, 9:44 p.m.