Triple
T5991721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheshire Golden Triangle |
E133364
|
entity |
| Predicate | oftenMentionedIn |
P5303
|
FINISHED |
| Object | British media |
—
|
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: British media | Statement: [Cheshire Golden Triangle, oftenMentionedIn, British media]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenMentionedIn Context triple: [Cheshire Golden Triangle, oftenMentionedIn, British media]
-
A.
mentionedWith
Indicates that two entities are mentioned together or in close association within the same context, such as a document, sentence, or conversation.
-
B.
frequentlyDiscussedIn
chosen
Indicates that a topic, subject, or entity is often the focus of conversation, debate, or mention within a particular context or medium.
-
C.
mentionedAs
Indicates that one entity is referred to or cited by name or description in the context of another entity.
-
D.
eraMentioned
Indicates that a specific historical or temporal era is explicitly referenced or mentioned in a given context.
-
E.
mentions
Indicates that one entity refers to, cites, or brings up another entity in some form of communication or content.
- 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_69c0087010d081908bb8142342d63330 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04e8fd030819095a4f3b3d425ec21 |
completed | March 22, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69c049e152e88190979ab80cb9b50321 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:05 p.m.