Triple
T29239887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | In the Shadow of Young Girls in Flower |
E741290
|
entity |
| Predicate | hasUrbanEpisodes |
P166774
|
FINISHED |
| Object | Parisian salons |
—
|
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: Parisian salons | Statement: [In the Shadow of Young Girls in Flower, hasUrbanEpisodes, Parisian salons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanEpisodes Context triple: [In the Shadow of Young Girls in Flower, hasUrbanEpisodes, Parisian salons]
-
A.
hasUrbanSectionsIn
Indicates that an entity includes or contains sections that are classified as urban within a specified area or region.
-
B.
hasUrbanFeature
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
-
C.
hasUrbanUnits
Indicates that an entity possesses or includes one or more urban units (such as cities, towns, or urbanized areas) within its scope or structure.
-
D.
hasUrbanVillages
Indicates that an entity contains or includes one or more designated urban villages within its area or jurisdiction.
-
E.
hasUrbanContinuity
Indicates that there is a continuous, uninterrupted urbanized area or built-up fabric between the related entities.
- 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_69f0911dd6fc819097d1abb287016489 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f6648570cc819095f42f2b8233d918 |
completed | May 2, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69f660f2e3708190ab658652bcfc04d0 |
completed | May 2, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69f661e9cb308190a56e25dc17df248e |
completed | May 2, 2026, 8:43 p.m. |
Created at: April 28, 2026, 12:30 p.m.