Triple
T9969172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Star Is Born film series |
E195758
|
entity |
| Predicate | hasRecurringCharacterType |
P10724
|
FINISHED |
| Object | aging male star mentor |
—
|
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: aging male star mentor | Statement: [A Star Is Born film series, hasRecurringCharacterType, aging male star mentor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecurringCharacterType Context triple: [A Star Is Born film series, hasRecurringCharacterType, aging male star mentor]
-
A.
hasRecurringElement
Indicates that an entity includes an element that appears repeatedly or occurs multiple times within it.
-
B.
hasRepetition
Indicates that something occurs, appears, or is performed more than once, showing recurrence or repeated instances within a given context.
-
C.
hasRecurringRole
Indicates that an entity repeatedly appears or participates in a role within an ongoing or multiple related contexts over time.
-
D.
hasRecurringSeriesProtagonists
Indicates that a recurring series features one or more protagonists who appear repeatedly across its installments.
-
E.
hasTypicalCharacterType
chosen
Indicates that an entity is commonly associated with or exemplified by a particular type of character or persona.
- 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_69ca82ebd1288190912f9e4482d1fa35 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb7b683ac8190ac97bd775a860d29 |
completed | April 2, 2026, 12:26 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9daa808190b413a1b9a1e929e2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:47 p.m.