Triple
T873462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daily Express |
E18864
|
entity |
| Predicate | hasNewspaperType |
P21126
|
FINISHED |
| Object | tabloid |
—
|
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: tabloid | Statement: [Daily Express, hasNewspaperType, tabloid]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNewspaperType Context triple: [Daily Express, hasNewspaperType, tabloid]
-
A.
magazineType
Indicates the specific category or genre to which a magazine belongs.
-
B.
isGazetteFor
Indicates that one entity serves as an official gazette or formal publication medium for another entity, typically used to announce or record official information, decisions, or notices.
-
C.
hasNewsPortal
Indicates that an entity operates, maintains, or is associated with a dedicated online news portal.
-
D.
hasCoverType
Indicates that one entity possesses or is associated with a specific type or category of cover.
-
E.
hasReadingType
Indicates that an entity is associated with a specific category or mode of reading, such as a particular interpretation, format, or type of reading measurement.
- 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_69a4938db1f081909bcd1ad2713b6096 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac97d0f88190b67fcb7fc058e4b9 |
completed | March 1, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69a4aa8b9b5c81909ac71904f8b8b5cd |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4abb157d08190a7d7281eb3f1b788 |
completed | March 1, 2026, 9:12 p.m. |
Created at: March 1, 2026, 7:39 p.m.