Triple
T22095828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ken Hood |
E546027
|
entity |
| Predicate | hasPrimaryThemeContext |
P56597
|
FINISHED |
| Object | interpersonal relationships |
—
|
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: interpersonal relationships | Statement: [Ken Hood, hasPrimaryThemeContext, interpersonal relationships]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryThemeContext Context triple: [Ken Hood, hasPrimaryThemeContext, interpersonal relationships]
-
A.
hasThemeType
Indicates that something is associated with or characterized by a particular thematic category or type.
-
B.
hasThemeConnection
Indicates a relationship where one entity is linked to another through a shared or related theme, topic, or conceptual focus.
-
C.
hasPrimary
Indicates that one entity is designated as the main or most important instance (the primary) in relation to another entity.
-
D.
centralThemeContext
chosen
Indicates that one concept serves as the main thematic focus within the situational, narrative, or discourse context defined by another.
-
E.
containsThemeArea
Indicates that one entity includes or encompasses a specific thematic area as part of its scope or content.
- 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e8f1f48190a5f1d9e96a6de688 |
completed | April 28, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69e71b20ec50819096ac196c798f8e3c |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:29 p.m.