Triple
T36364554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Lilian Thurman |
E895582
|
entity |
| Predicate | helpsFrame |
P185168
|
FINISHED |
| Object | film’s psychological themes |
—
|
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: film’s psychological themes | Statement: [Dr. Lilian Thurman, helpsFrame, film’s psychological themes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpsFrame Context triple: [Dr. Lilian Thurman, helpsFrame, film’s psychological themes]
-
A.
helpsIn
Indicates that one entity provides assistance, support, or aid to another entity in performing or achieving a particular task, activity, or goal.
-
B.
helpsGroup
Indicates that one entity provides assistance or support to a group of entities.
-
C.
laterHelps
Indicates that one entity provides help or assistance to another at a subsequent time rather than immediately.
-
D.
helpedForm
Indicates that one entity contributed significantly to the creation, establishment, or founding of another entity.
-
E.
usesFrame
Indicates that one entity employs, relies on, or is structured around a particular frame, framework, or reference structure provided by another entity.
- F. None of above. chosen
Provenance (4 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_69f76e5044248190b390d8887dc03254 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7bb3ff1b08190802b1063d55d3923 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a611a081908dd6aec1df3f4d7f |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7bb3f23f48190b0b9c2d667e09b52 |
completed | May 3, 2026, 9:16 p.m. |
Created at: May 3, 2026, 4:10 p.m.