Triple
T35154287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tru |
E1015075
|
entity |
| Predicate | portraysAspectOfLifeOf |
P193404
|
FINISHED |
| Object | Truman Capote's later years |
—
|
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: Truman Capote's later years | Statement: [Tru, portraysAspectOfLifeOf, Truman Capote's later years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysAspectOfLifeOf Context triple: [Tru, portraysAspectOfLifeOf, Truman Capote's later years]
-
A.
portraysActivity
Indicates that one entity visually or narratively represents another entity engaged in a particular activity.
-
B.
includesLifeOf
chosen
Indicates that one entity encompasses, covers, or contains the entire lifespan, life events, or life-related aspects of another entity.
-
C.
portraysPersonAs
Indicates that one entity represents, depicts, or characterizes another person in a particular way or role.
-
D.
followsLifeOf
Indicates that one entity’s narrative, development, or progression is tracked or depicted over the course of that entity’s life.
-
E.
controlsAspectOfLife
Indicates that one entity has power or authority to determine, regulate, or strongly influence a particular aspect or domain of another entity’s life.
- 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_69f76ddb3a708190b521ba2970b17178 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff397e19a88190a945b826159f5290 |
completed | May 9, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69ff392400d0819088d30d08d4a774bd |
completed | May 9, 2026, 1:39 p.m. |
Created at: May 3, 2026, 4:02 p.m.