Triple
T28935024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsawwassen Springs Golf Course |
E733888
|
entity |
| Predicate | hasTypeOfGrass |
P44260
|
FINISHED |
| Object | turfgrass suitable for coastal British Columbia |
—
|
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: turfgrass suitable for coastal British Columbia | Statement: [Tsawwassen Springs Golf Course, hasTypeOfGrass, turfgrass suitable for coastal British Columbia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfGrass Context triple: [Tsawwassen Springs Golf Course, hasTypeOfGrass, turfgrass suitable for coastal British Columbia]
-
A.
hasGrass
Indicates that one entity possesses or is covered by grass.
-
B.
hasGrassEquivalent
Indicates that one entity corresponds to or serves as the grass-based counterpart or equivalent of another entity.
-
C.
hasGrassTypeGreens
Indicates that something possesses or includes green vegetation or grassy plant material.
-
D.
fairwayGrassType
chosen
Indicates the type or variety of grass used on a golf course fairway.
-
E.
isGrassSubfamily
Indicates that one entity is a botanical subfamily within the grass family (Poaceae) to which the other entity belongs.
- 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_69f05b0b49b08190b8994b339c7980f6 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69fd57ba740c8190bd1d40166fccccb7 |
completed | May 8, 2026, 3:25 a.m. |
| PD | Predicate disambiguation | batch_69fd55ee82b881908a639da3a41b3af6 |
completed | May 8, 2026, 3:18 a.m. |
Created at: April 28, 2026, 8:31 a.m.