Triple
T592327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyannisport Club |
E17302
|
entity |
| Predicate | greensType |
P12060
|
FINISHED |
| Object | bentgrass greens |
—
|
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: bentgrass greens | Statement: [Hyannisport Club, greensType, bentgrass greens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: greensType Context triple: [Hyannisport Club, greensType, bentgrass greens]
-
A.
greenType
chosen
Indicates that one entity is classified as a specific type or category within the broader concept of "green" (e.g., a subtype, variant, or classification related to greenness).
-
B.
evergreen
Indicates that something remains persistently relevant, active, or unchanged over time, without becoming outdated or obsolete.
-
C.
growsIn
Indicates that one entity develops, thrives, or increases in size or number within a specified environment, medium, or location.
-
D.
listsGrounds
Indicates that one entity enumerates or specifies the reasons, bases, or justifications (grounds) associated with another entity.
-
E.
plantType
Indicates the specific kind or category of plant that an entity is classified as.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bbaf53081908eed240bed09f63b |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494cd7d3c8190af008acf34a2293b |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.