Triple
T18037894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dayton Daily News |
E431558
|
entity |
| Predicate | hasBusinessSection |
P129544
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Dayton Daily News, hasBusinessSection, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBusinessSection Context triple: [Dayton Daily News, hasBusinessSection, yes]
-
A.
hasBusiness
Indicates that one entity owns, operates, or is formally associated with a business entity.
-
B.
hasBusinessDivision
Indicates that an organization includes or is composed of a specific business division as a subordinate unit.
-
C.
hasIndustrySection
Indicates that an entity belongs to, is categorized under, or is associated with a particular industry section.
-
D.
hasBusinessIn
Indicates that one entity conducts, operates, or maintains business activities within the jurisdiction, location, or domain of another entity.
-
E.
hasBusinesses
Indicates that an entity owns, operates, or is associated with one or more businesses.
- 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4be3bc3208190a6db569e79f06232 |
completed | April 19, 2026, 11:36 a.m. |
| PD | Predicate disambiguation | batch_69e3f908da508190a088aa837ea5b7af |
completed | April 18, 2026, 9:35 p.m. |
| PDg | Predicate description generation | batch_69e42d8eefa88190a700c7c1b4213e46 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:25 a.m.