Triple
T31186160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Amateur |
E795049
|
entity |
| Predicate | hostPattern |
P8688
|
FINISHED |
| Object | rotating venues within the United Kingdom |
—
|
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: rotating venues within the United Kingdom | Statement: [The Amateur, hostPattern, rotating venues within the United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostPattern Context triple: [The Amateur, hostPattern, rotating venues within the United Kingdom]
-
A.
locationPattern
chosen
Indicates a recurring or structured spatial relationship, where an entity consistently appears or is arranged in a particular type of location or spatial configuration.
-
B.
URLPattern
Indicates that a resource or endpoint is identified or matched by a specific structured web address pattern.
-
C.
hatPattern
Indicates that one entity has a hat characterized by a specific pattern or design.
-
D.
termPattern
Indicates a relationship where one term follows or matches a specific structural or lexical pattern defined by another term or template.
-
E.
languagePattern
Indicates a recurring or structured way in which language is used, organized, or formed within a given context.
- 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_69f224d675d08190957198068e440422 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c234d648190a243fb2b107136a9 |
completed | May 3, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69f69665cd9c819088c388fc82fec42e |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 9:08 p.m.