Triple
T270222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fireside Poets |
E5615
|
entity |
| Predicate | readership |
P9917
|
FINISHED |
| Object | American households |
—
|
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: American households | Statement: [Fireside Poets, readership, American households]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readership Context triple: [Fireside Poets, readership, American households]
-
A.
popularity
Indicates how widely liked, admired, or favored something or someone is by a group of people.
-
B.
USViewers
Indicates the number or set of viewers located in the United States who watched or were exposed to a particular piece of content or event.
-
C.
audienceSizeApproximate
Indicates an estimated or approximate number of people in the audience for an event or content.
-
D.
follows
Indicates that one entity comes after, moves behind, or acts in accordance with another entity in time, space, or sequence.
-
E.
fareMedia
Indicates that a particular type of ticket, pass, or payment instrument is used as the medium for paying a fare.
- 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_69a25853594c8190b05ec3a586ec88bf |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25e69a9248190b9e7959b43223baa |
completed | Feb. 28, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69a25b721180819080d43c43fcbccf87 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25e68f0408190bfc851c32d6eebf3 |
completed | Feb. 28, 2026, 3:18 a.m. |
Created at: Feb. 28, 2026, 2:57 a.m.