Triple
T26422921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Shambles Market |
E664288
|
entity |
| Predicate | setAmid |
P160742
|
FINISHED |
| Object | medieval streets of York |
—
|
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: medieval streets of York | Statement: [The Shambles Market, setAmid, medieval streets of York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setAmid Context triple: [The Shambles Market, setAmid, medieval streets of York]
-
A.
setAround
Indicates that one entity is positioned or arranged surrounding another entity or a central point.
-
B.
setWith
Indicates that one entity is grouped, combined, or associated together in a set or collection with another entity.
-
C.
setBetween
Indicates that one entity is positioned or defined as lying between two other entities in some ordered or spatial context.
-
D.
setInPart
Indicates that something is located or placed within a specific part or section of a larger whole.
-
E.
setsOn
Indicates that one entity places or arranges another entity onto a specified surface, container, or context.
- F. None of above. chosen
Provenance (4 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_69ee883a04ec81908883c4559f8c7e24 |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f611b747e48190a20de2bc49ad29ef |
completed | May 2, 2026, 3:01 p.m. |
| PD | Predicate disambiguation | batch_69f602d5c8808190a1fdbebd6f0981e8 |
completed | May 2, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69f604120e848190b516c29b781d19cc |
completed | May 2, 2026, 2:02 p.m. |
Created at: April 26, 2026, 11:44 p.m.