Triple
T34701651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parks Road, Oxford |
E1000385
|
entity |
| Predicate | hasLandmarkAtJunction |
P184542
|
FINISHED |
| Object | King’s Arms public house |
—
|
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: King’s Arms public house | Statement: [Parks Road, Oxford, hasLandmarkAtJunction, King’s Arms public house]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandmarkAtJunction Context triple: [Parks Road, Oxford, hasLandmarkAtJunction, King’s Arms public house]
-
A.
atJunctionOf
chosen
Indicates that something is located at or directly connected to the point where two or more paths, roads, or lines meet.
-
B.
trailJunctionOf
Indicates that one trail serves as a junction or connecting point between two or more other trails.
-
C.
nearJunctionOf
Indicates that one entity is located close to the point where two or more linear features (such as roads, tracks, or paths) meet or intersect.
-
D.
isMajorRoadJunction
Indicates that a location serves as a primary intersection where major roads or highways meet or cross.
-
E.
hasJunctionWith
Indicates that one entity meets or intersects with another at a shared junction point.
- 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_69f76dab937881909c86f1b9ad50445f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69ff4de66ba481908e7184b3cf9d4d2d |
completed | May 9, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69ff4c702a5881909c6684c74807e945 |
completed | May 9, 2026, 3:02 p.m. |
Created at: May 3, 2026, 3:59 p.m.