Triple
T25742757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ewloe Castle |
E648261
|
entity |
| Predicate | locatedInWoodland |
P39061
|
FINISHED |
| Object | Wepre Wood |
—
|
NE NERFINISHED |
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: Wepre Wood | Statement: [Ewloe Castle, locatedInWoodland, Wepre Wood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInWoodland Context triple: [Ewloe Castle, locatedInWoodland, Wepre Wood]
-
A.
locatedInForest
chosen
Indicates that an entity is situated within the boundaries of a forest.
-
B.
hasNearbyWoodland
Indicates that one entity is located close to or in the immediate vicinity of a woodland area associated with another entity.
-
C.
locatedInParkLikeSetting
Indicates that something is situated within or directly surrounded by an environment resembling a park, typically featuring natural or landscaped outdoor elements.
-
D.
isForested
Indicates that an area or region is covered predominantly by forest or dense tree vegetation.
-
E.
Forest
Indicates that an entity is located in, associated with, or characterized as being within a forested area.
- F. None of above.
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_69e7ab306eec8190b05c312c6ab186b8 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
Created at: April 22, 2026, 3:46 a.m.