Triple
T7633519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Good Pope John |
E172817
|
entity |
| Predicate | hasAffectionateConnotation |
P4340
|
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: [Good Pope John, hasAffectionateConnotation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAffectionateConnotation Context triple: [Good Pope John, hasAffectionateConnotation, true]
-
A.
hasConnotation
chosen
Indicates that one entity carries an implied or associated meaning, tone, or emotional nuance in relation to another entity.
-
B.
hasAffectionateNicknameFor
Indicates that one entity uses or assigns a fond, affectionate, or endearing nickname to another entity.
-
C.
honorificConnotation
Indicates that one entity refers to or characterizes another using an honorific or respectful form, conveying deference or elevated social status.
-
D.
isSympatheticTo
Indicates that one entity feels or expresses compassion, understanding, or emotional support toward another entity.
-
E.
emotionallyAttachedTo
Indicates that one entity has a strong emotional bond, affection, or dependence directed toward another 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_69c69952849881908fdcea7a93bfc307 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6faa72f2881908479049dd8d181a4 |
completed | March 27, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e8cadc8190b7977fcd213954dd |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:57 p.m.