Triple
T29292815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liberty Park (Clarksville, Tennessee) |
E742726
|
entity |
| Predicate | hasSportsFields |
P33887
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Liberty Park (Clarksville, Tennessee), hasSportsFields, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSportsFields Context triple: [Liberty Park (Clarksville, Tennessee), hasSportsFields, true]
-
A.
hasSportsGround
chosen
Indicates that an entity possesses, includes, or is associated with a sports ground or athletic field as part of its facilities or area.
-
B.
hasSportsFunction
Indicates that an entity serves a role, purpose, or function related to sports activities or sports-related operations.
-
C.
hasSportsVenueType
Indicates that a sports venue is classified as being of a specific type or category (e.g., stadium, arena, court).
-
D.
hasSportsPrecinct
Indicates that an entity includes, contains, or is associated with a designated area or complex specifically intended for sports activities or facilities.
-
E.
hasProfessionalSportsVenue
Indicates that one entity possesses or hosts a venue specifically used for professional sports events.
- 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_69f0912323c48190b9a24ef8cf359225 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
Created at: April 28, 2026, 1:03 p.m.