Triple
T19128059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucas |
E468237
|
entity |
| Predicate | sportsTheme |
P6214
|
FINISHED |
| Object | American football |
—
|
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: American football | Statement: [Lucas, sportsTheme, American football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportsTheme Context triple: [Lucas, sportsTheme, American football]
-
A.
sportFocus
chosen
Indicates that one entity has a primary emphasis, specialization, or concentration on a particular sport represented by the other entity.
-
B.
sportCreated
Indicates that an entity is the originator or inventor of a particular sport.
-
C.
sportsCategory
Indicates that one entity is classified as a type or category within the domain of sports to which the other entity belongs.
-
D.
popularSport
Indicates that a sport is widely liked, followed, or played by many people within a certain group or region.
-
E.
sportsModel
Indicates a relationship where an entity is a sports-oriented model or variant of another entity (such as a product, design, or system) optimized or styled for sporting use.
- 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_69d8dd0796a48190b34ce4cd9d3f3be5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e3ceb5808190b3b53d9e8df3605a |
completed | April 20, 2026, 8:29 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b085288190b974d649e12e0844 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:05 p.m.