Triple
T19871411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nevada tourism |
E477524
|
entity |
| Predicate | hasKeySegment |
P116746
|
FINISHED |
| Object | gaming tourism |
—
|
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: gaming tourism | Statement: [Nevada tourism, hasKeySegment, gaming tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKeySegment Context triple: [Nevada tourism, hasKeySegment, gaming tourism]
-
A.
hasSegmentWith
chosen
Indicates that an entity contains or includes at least one segment that satisfies a specified condition or matches a given segment.
-
B.
hasRegularSegment
Indicates that an entity includes or is associated with a segment that occurs in a consistent, repeating, or standard pattern.
-
C.
hasSegmentOn
Indicates that one entity includes or occupies a specific segment or portion on another entity (such as a line, path, or sequence).
-
D.
hasSegmentBasedOn
Indicates that one segment is derived from, modeled after, or constructed using another segment as its basis.
-
E.
hasSegmentStatus
Indicates that a specific segment within a larger whole is associated with a particular status or condition.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658a3d2b08190ad81914d4860df0e |
completed | April 20, 2026, 4:47 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:51 p.m.