Triple
T3827058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lara Beach |
E88714
|
entity |
| Predicate | hasTypicalSummerActivity |
P1164
|
FINISHED |
| Object | swimming |
—
|
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: swimming | Statement: [Lara Beach, hasTypicalSummerActivity, swimming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalSummerActivity Context triple: [Lara Beach, hasTypicalSummerActivity, swimming]
-
A.
hasRecreationActivity
Indicates that an entity provides, includes, or is associated with a particular recreational activity.
-
B.
hasWaterActivity
Indicates that one entity possesses, exhibits, or is characterized by a particular level or type of water-related activity (such as moisture content, water availability, or water-based processes).
-
C.
typicalActivity
chosen
Indicates that an entity is commonly or characteristically engaged in a particular activity.
-
D.
hasRecreationalOrganization
Indicates that an entity is associated with, or hosts, a recreational organization such as a club, team, or leisure group.
-
E.
hasPopularActivity
Indicates that an entity is associated with an activity that is widely favored, frequently engaged in, or well-liked by many people.
- 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_69aed9538cf881909d9ce8ca4ac7c18c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb8459f881908a2c91bb07e381ef |
completed | March 9, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69aee74c2e04819094b94b3c0bac1806 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.