Triple
T35778736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burnham, Buckinghamshire, England |
E1034372
|
entity |
| Predicate | notableWoodlandNearby |
P115557
|
FINISHED |
| Object | Burnham Beeches |
E345051
|
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: Burnham Beeches | Statement: [Burnham, Buckinghamshire, England, notableWoodlandNearby, Burnham Beeches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableWoodlandNearby Context triple: [Burnham, Buckinghamshire, England, notableWoodlandNearby, Burnham Beeches]
-
A.
hasNearbyWoodland
chosen
Indicates that one entity is located close to or in the immediate vicinity of a woodland area associated with another entity.
-
B.
nearbyHeathland
Indicates that one entity is located close to or adjacent to a heathland area.
-
C.
nearNationalForest
Indicates that one entity is located close to, but not necessarily inside, a designated national forest area.
-
D.
hasNearbyForestType
Indicates that one entity is located close to, or in the vicinity of, a forest of a specified type.
-
E.
hasNearbyWildernessArea
Indicates that a wilderness area is located within a close geographic proximity to the referenced place or entity.
- F. None of above.
Provenance (4 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_69f76e14a1e081908eddd57bd6fdb3be |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a38915e091c8190b7cd3c7959acccb0 |
completed | June 22, 2026, 1:35 a.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:06 p.m.