Triple
T572785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trinity College, Cambridge |
E13697
|
entity |
| Predicate | gardens |
P949
|
FINISHED |
| Object | extensive college gardens along the Backs |
—
|
LITERAL 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: extensive college gardens along the Backs | Statement: [Trinity College, Cambridge, gardens, extensive college gardens along the Backs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gardens Context triple: [Trinity College, Cambridge, gardens, extensive college gardens along the Backs]
-
A.
hasGardenType
Indicates that an entity possesses or is associated with a garden of a specified type.
-
B.
involvesPlant
Indicates that the relationship or action includes or pertains to a plant as a participating entity.
-
C.
crop
Indicates the action of cutting or trimming part of an object or image, typically to remove unwanted outer areas while keeping a selected region.
-
D.
plantType
Indicates the specific kind or category of plant that an entity is classified as.
-
E.
vegetation
chosen
Indicates that an area or object is covered with, contains, or is characterized by plant life.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b49bad88190bc73d31a317c0ef4 |
completed | March 1, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69a494c4969c819080375d08f9eec50c |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.