Triple
T12108615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Inquirer |
E288364
|
entity |
| Predicate | fictionalCirculationScope |
P103335
|
FINISHED |
| Object | metropolitan New 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: metropolitan New York | Statement: [New York Inquirer, fictionalCirculationScope, metropolitan New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalCirculationScope Context triple: [New York Inquirer, fictionalCirculationScope, metropolitan New York]
-
A.
fictionalStatus
Indicates that an entity exists only in imagination or narrative and does not correspond to a real-world counterpart.
-
B.
fictionalOrigin
Indicates that one entity originates from, or was first introduced within, a fictional work, universe, or narrative created by another entity.
-
C.
fictionalMedium
Indicates that a work of fiction is presented or conveyed through a particular medium or format (such as a book, film, game, or comic).
-
D.
fictionalGenre
Indicates that a work of fiction belongs to or is categorized under a particular narrative genre or style.
-
E.
fictionalUniverse
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
- 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9164ada5081908676bd9e5947268a |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150497408190921334d21503375a |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d916481a008190ae66677b9e6dd961 |
completed | April 10, 2026, 3:24 p.m. |
Created at: April 8, 2026, 9:49 p.m.