Triple
T3292607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fakenham Racecourse |
E69135
|
entity |
| Predicate | hasBettingFacilities |
P12416
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Fakenham Racecourse, hasBettingFacilities, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBettingFacilities Context triple: [Fakenham Racecourse, hasBettingFacilities, yes]
-
A.
hasCasino
Indicates that an entity includes, contains, or is associated with a casino facility or gambling establishment.
-
B.
betting
Indicates engaging in a wager where one party risks something of value on the outcome of an uncertain event involving another entity.
-
C.
hasFacilities
chosen
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
-
D.
hasBackstageFacilities
Indicates that a venue or location provides backstage areas and related facilities for performers or staff.
-
E.
usedInBettingLines
Indicates that something (such as data, statistics, or an event) is employed as a factor or component in determining betting lines or odds.
- 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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb07379dc8190b7bb409bcf42bdd6 |
completed | March 8, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69ada42407dc81909f60d7a14e1b7934 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:10 p.m.