Triple
T32637331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucy |
E834380
|
entity |
| Predicate | emotionalSignificanceToWendy |
P41499
|
FINISHED |
| Object | primary source of comfort |
—
|
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: primary source of comfort | Statement: [Lucy, emotionalSignificanceToWendy, primary source of comfort]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emotionalSignificanceToWendy Context triple: [Lucy, emotionalSignificanceToWendy, primary source of comfort]
-
A.
hasParticularSignificanceFor
chosen
Indicates that something holds a special, notable, or contextually important relevance or impact for a particular entity or situation.
-
B.
emotionallyAttachedTo
Indicates that one entity has a strong emotional bond, affection, or dependence directed toward another entity.
-
C.
emotionalFocusOf
Indicates that one entity is the primary target or center of another entity’s emotions or emotional attention.
-
D.
emotionTowardsWife
Indicates that a person experiences or expresses a particular emotion directed toward their wife.
-
E.
objectOfAffectionFor
Indicates that one entity is the target or recipient of another entity’s romantic or affectionate feelings.
- 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_69f3492dc2308190a88c6e30a3f3f576 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c775d6188190b236fc4f89a11b61 |
completed | May 3, 2026, 3:56 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f617c08190a70ba880210f908c |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 1:07 a.m.