Triple
T8405163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snug Harbor, New Jersey |
E198476
|
entity |
| Predicate | typicalRecreation |
P971
|
FINISHED |
| Object | boating |
—
|
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: boating | Statement: [Snug Harbor, New Jersey, typicalRecreation, boating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRecreation Context triple: [Snug Harbor, New Jersey, typicalRecreation, boating]
-
A.
typicalActivity
Indicates that an entity is commonly or characteristically engaged in a particular activity.
-
B.
hasRecreationActivity
chosen
Indicates that an entity provides, includes, or is associated with a particular recreational activity.
-
C.
hasRecreationPurpose
Indicates that something is used or intended to be used for recreational or leisure activities.
-
D.
outdoorActivityType
Indicates the specific kind of outdoor activity associated with an entity or event.
-
E.
hasRecreationalOrganization
Indicates that an entity is associated with, or hosts, a recreational organization such as a club, team, or leisure group.
- 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_69ca8310df9c8190b25f16161cca3e41 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb83116bf48190894bd5d5465520ef |
completed | March 31, 2026, 8:17 a.m. |
| PD | Predicate disambiguation | batch_69cb70d473dc8190af8ea81ee5aa970d |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:05 p.m.