Triple
T16877585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gloria |
E421337
|
entity |
| Predicate | widelyCovered |
P75882
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Gloria, widelyCovered, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: widelyCovered Context triple: [Gloria, widelyCovered, true]
-
A.
widelyCoveredBy
chosen
Indicates that something (such as an event, topic, or issue) receives extensive attention or reporting from many media outlets or information sources.
-
B.
isFrequentlyCovered
Indicates that an entity is regularly or commonly reported on, discussed, or featured, especially in media or informational sources.
-
C.
isCoveredIn
Indicates that one entity has its surface or area overlaid, coated, or blanketed by another substance or material.
-
D.
typicallyCovers
Indicates that one entity is the kind of thing that usually or normally includes, addresses, or encompasses another entity.
-
E.
alsoCovers
Indicates that something extends its scope or applicability to include an additional subject, area, or case beyond what was originally covered.
- 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3b7f8a1d48190ad829f86e235a1d0 |
completed | April 18, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69e32b90ec3c819099c51bb7baf2984c |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:29 a.m.