Triple
T537223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Playa Negra (Vieques) |
E12351
|
entity |
| Predicate | hasTypicalActivity |
P1164
|
FINISHED |
| Object | day visits |
—
|
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: day visits | Statement: [Playa Negra (Vieques), hasTypicalActivity, day visits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalActivity Context triple: [Playa Negra (Vieques), hasTypicalActivity, day visits]
-
A.
typicalActivity
chosen
Indicates that an entity is commonly or characteristically engaged in a particular activity.
-
B.
activityTime
Indicates the time period during which an activity occurs or is scheduled to take place.
-
C.
hasRecreationActivity
Indicates that an entity provides, includes, or is associated with a particular recreational activity.
-
D.
hasActivityStatus
Indicates the current state or condition of an activity, such as whether it is planned, ongoing, completed, or cancelled.
-
E.
hasMissionActivity
Indicates that an entity is associated with, performs, or is involved in a specific mission-related 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_69a4933208e88190891f5debab1b776d |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4985e51908190a34aa82ea9dbee1e |
completed | March 1, 2026, 7:49 p.m. |
| PD | Predicate disambiguation | batch_69a494b51ff08190a39f4168fd9a7ddf |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.