Triple
T5071599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AFI Award for Best Actress in a Lead Role |
E114292
|
entity |
| Predicate | roleFocus |
P31
|
FINISHED |
| Object | lead performance |
—
|
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: lead performance | Statement: [AFI Award for Best Actress in a Lead Role, roleFocus, lead performance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleFocus Context triple: [AFI Award for Best Actress in a Lead Role, roleFocus, lead performance]
-
A.
role
Indicates the function, position, or responsibility that one entity holds in relation to another within a given context.
-
B.
roleInText
Indicates that an entity participates in a text with a specific function or capacity (e.g., author, editor, character).
-
C.
roleCharacteristic
Indicates that a particular characteristic, quality, or attribute is associated with and helps define a given role or function.
-
D.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
E.
categoryFocus
Indicates that one entity is the primary subject, theme, or focal point within the broader category defined by the other 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_69bd443cf28c8190ad371d603563dbdd |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74ce140881909a2874663244c0db |
completed | March 20, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69bd7157fe608190b4515d56fdd0a616 |
completed | March 20, 2026, 4:10 p.m. |
Created at: March 20, 2026, 1:39 p.m.