Triple
T20489659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quincy Shore Drive |
E502704
|
entity |
| Predicate | hasRecreationRole |
P80753
|
FINISHED |
| Object | access road for Wollaston Beach |
—
|
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: access road for Wollaston Beach | Statement: [Quincy Shore Drive, hasRecreationRole, access road for Wollaston Beach]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecreationRole Context triple: [Quincy Shore Drive, hasRecreationRole, access road for Wollaston Beach]
-
A.
hasRecreationType
Indicates that an entity is associated with or offers a particular type or category of recreational activity.
-
B.
hasRecreationValue
Indicates that something provides opportunities or benefits for leisure, enjoyment, or recreational activities.
-
C.
hasRecreationPurpose
chosen
Indicates that something is used or intended to be used for recreational or leisure activities.
-
D.
hasRecreationActivity
Indicates that an entity provides, includes, or is associated with a particular recreational activity.
-
E.
hasRecreationClassification
Indicates that an entity is assigned a specific type or category of recreational use or activity.
- 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_69e0b4b0373881909dd3e9387f82eab4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69b5d93ec81908259696359090b35 |
completed | April 20, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69e59fcdf6e08190a604204615dc56e6 |
completed | April 20, 2026, 3:38 a.m. |
Created at: April 16, 2026, 11:34 a.m.