Triple
T5298312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The White City |
E119909
|
entity |
| Predicate | usedToHighlight |
P41972
|
FINISHED |
| Object | architectural heritage of Arequipa |
—
|
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: architectural heritage of Arequipa | Statement: [The White City, usedToHighlight, architectural heritage of Arequipa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedToHighlight Context triple: [The White City, usedToHighlight, architectural heritage of Arequipa]
-
A.
isUsedToIllustrate
chosen
Indicates that one entity serves as an example or demonstration to clarify, explain, or represent another entity.
-
B.
usedMark
Indicates that one entity has employed or applied a particular mark, symbol, or indicator in some context or action.
-
C.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
D.
usedToExplain
Indicates that one entity serves as an explanation or clarification for another entity.
-
E.
usesIndicator
Indicates that one entity employs or relies on another entity as an indicator, signal, or metric for assessment, decision-making, or interpretation.
- 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_69bd446f22b88190b6a47fb91c68a3e7 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8e44e7c881909b241b2fec366038 |
completed | March 20, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69bd845097ac81909678624c4907fda4 |
completed | March 20, 2026, 5:30 p.m. |
Created at: March 20, 2026, 1:53 p.m.