Triple
T15971689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Marriage Counselor |
E387338
|
entity |
| Predicate | hasTaglineTheme |
P7688
|
FINISHED |
| Object | every marriage has challenges |
—
|
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: every marriage has challenges | Statement: [The Marriage Counselor, hasTaglineTheme, every marriage has challenges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTaglineTheme Context triple: [The Marriage Counselor, hasTaglineTheme, every marriage has challenges]
-
A.
hasTagline
chosen
Indicates that an entity is associated with a specific slogan or tagline that represents or promotes it.
-
B.
taglineForm
Indicates that one entity serves as the tagline or slogan associated with another entity.
-
C.
taglineMatch
Indicates that two entities share the same tagline or that a tagline corresponds to a given entity.
-
D.
hasMarketingTheme
Indicates that an entity is associated with or characterized by a particular marketing theme or campaign concept.
-
E.
hasSloganType
Indicates the specific category or type of slogan associated with an entity.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142d6fb588190b4176eab4bbae774 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:54 a.m.