Triple
T28183514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexican Spitfire film series |
E716105
|
entity |
| Predicate | basedOnCharacterIntroducedIn |
P116161
|
FINISHED |
| Object | The Girl from Mexico |
—
|
NE NERFINISHED |
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: The Girl from Mexico | Statement: [Mexican Spitfire film series, basedOnCharacterIntroducedIn, The Girl from Mexico]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnCharacterIntroducedIn Context triple: [Mexican Spitfire film series, basedOnCharacterIntroducedIn, The Girl from Mexico]
-
A.
introducedByCharacter
Indicates that one character is responsible for presenting, bringing into the story, or otherwise causing another entity to be first revealed or made known.
-
B.
introducedByCharacters
Indicates that something (such as an idea, object, or event) is brought into the narrative or context by specific characters.
-
C.
featuresCharacterDebut
chosen
Indicates that the subject work includes the first-ever appearance of a particular character.
-
D.
characterFirstAppearanceInThisPortrayal
Indicates that this is the first time the character appears in the specific portrayal or adaptation being referenced.
-
E.
recurringCharacterIntroduced
Indicates that a character is introduced in a work as one who appears repeatedly across multiple episodes, issues, or installments.
- 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_69efd6b4fc5c81909dd88f01a8c2b35d |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
Created at: April 27, 2026, 10:21 p.m.