Triple
T8457256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcadet – Poissonniers |
E199949
|
entity |
| Predicate | hasNetworkStyle |
P1609
|
FINISHED |
| Object | Paris Métro Art Nouveau and modern styles |
—
|
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: Paris Métro Art Nouveau and modern styles | Statement: [Marcadet – Poissonniers, hasNetworkStyle, Paris Métro Art Nouveau and modern styles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNetworkStyle Context triple: [Marcadet – Poissonniers, hasNetworkStyle, Paris Métro Art Nouveau and modern styles]
-
A.
hasBroadcastStyle
Indicates that one entity is characterized by, or associated with, a particular manner or style of broadcasting.
-
B.
hasSystemStyle
Indicates that one entity is associated with, or characterized by, a particular system-defined style of another entity.
-
C.
hasStyle
chosen
Indicates that an entity possesses, exhibits, or is characterized by a particular style or manner.
-
D.
hasPrimaryNetwork
Indicates that an entity is associated with or connected to its main or most important network among potentially multiple networks.
-
E.
hasContractStyle
Indicates that one entity is associated with or characterized by a particular contract style or contractual format.
- 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe48f180c8190a71cf9d7248ade60 |
completed | March 31, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69cbd0fc634481909842c0a30077bfde |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:10 p.m.