Triple
T20162765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salisbury Park trails |
E491752
|
entity |
| Predicate | approximateUse |
P97474
|
FINISHED |
| Object | local recreation |
—
|
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: local recreation | Statement: [Salisbury Park trails, approximateUse, local recreation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateUse Context triple: [Salisbury Park trails, approximateUse, local recreation]
-
A.
hasApproximateUse
chosen
Indicates that one entity is used for a purpose that is similar to, but not exactly the same as, the use or function of another entity.
-
B.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
-
C.
approximateEndUse
Indicates that something is an estimated or inferred final purpose, application, or consumption context of another entity.
-
D.
estimatedUsing
Indicates that one entity’s value, state, or outcome is derived by applying an estimation method, model, or procedure based on another entity.
-
E.
approximateEstimation
Indicates an estimation relationship where one value or assessment is only roughly or closely, but not exactly, equal to another.
- 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667e505888190a05e26a3c5a0ede1 |
completed | April 20, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69e55b0c11cc8190836d1eee5945f000 |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:34 p.m.