Triple
T1438190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trivia, or the Art of Walking the Streets of London |
E31003
|
entity |
| Predicate | contemporaryReception |
P29313
|
FINISHED |
| Object | popular |
—
|
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: popular | Statement: [Trivia, or the Art of Walking the Streets of London, contemporaryReception, popular]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contemporaryReception Context triple: [Trivia, or the Art of Walking the Streets of London, contemporaryReception, popular]
-
A.
contemporary
Indicates that two entities exist, occur, or are active during the same time period or historical era.
-
B.
historicalReception
Indicates how an event, work, or figure was received, interpreted, or evaluated by people and institutions over time.
-
C.
hasCulturalReception
Indicates that an entity has been received, interpreted, or responded to within a particular cultural context or by a specific audience.
-
D.
contemporaryWith
Indicates that two entities existed, occurred, or were active during the same time period.
-
E.
marketReception
Indicates how a product, service, or work is received, evaluated, and responded to by the market or audience after its introduction.
- 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_69a4991633388190a4d61b5a98aa407a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c5ff8dbc81909eafcfc9f2260a22 |
completed | March 1, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69a4c478f65481909ee716791c663491 |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c5fd2c5c81909283b7a74aff89b7 |
completed | March 1, 2026, 11:04 p.m. |
Created at: March 1, 2026, 8 p.m.