Triple
T38139810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Treat People with Kindness |
E952446
|
entity |
| Predicate | hasSloganUsage |
P6980
|
FINISHED |
| Object | Treat People with Kindness slogan |
—
|
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: Treat People with Kindness slogan | Statement: [Treat People with Kindness, hasSloganUsage, Treat People with Kindness slogan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSloganUsage Context triple: [Treat People with Kindness, hasSloganUsage, Treat People with Kindness slogan]
-
A.
hasSloganType
Indicates the specific category or type of slogan associated with an entity.
-
B.
hasSloganLanguage
Indicates that a slogan is expressed or written in a particular language.
-
C.
hasAdvertisingSlogan
Indicates that an entity uses or is associated with a particular advertising slogan as part of its promotional or branding activities.
-
D.
sloganUsedIn
chosen
Indicates that a particular slogan is employed or featured within a specific context, such as a campaign, advertisement, or organization.
-
E.
hasSloganOrKeyPhrase
Indicates that an entity is associated with a specific slogan, tagline, or key phrase used to represent or promote it.
- 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_69f76f09a7148190a4b91c0bacdc127a |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcb089a8f881909aa9e722babd43f7 |
completed | May 7, 2026, 3:32 p.m. |
| PD | Predicate disambiguation | batch_69fc45666c5c8190913bd632ac0e5b84 |
completed | May 7, 2026, 7:55 a.m. |
Created at: May 3, 2026, 4:21 p.m.