Triple
T27131966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 9 Songs |
E681583
|
entity |
| Predicate | mainFemaleCharacterNationality |
P15237
|
FINISHED |
| Object | American |
—
|
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: American | Statement: [9 Songs, mainFemaleCharacterNationality, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainFemaleCharacterNationality Context triple: [9 Songs, mainFemaleCharacterNationality, American]
-
A.
protagonistNationality
Indicates the country or national identity to which the protagonist of a work is associated or belongs.
-
B.
hasFemaleCharacter
Indicates that an entity includes or features at least one female character.
-
C.
nationalityInStory
chosen
Indicates that a character or entity in a narrative is associated with a particular nationality within the context of that story.
-
D.
protagonistEthnicity
Indicates the ethnic background or cultural heritage associated with a work’s main character.
-
E.
femaleLeadCharacterStatus
Indicates the narrative or role status assigned to a female lead character within a story or production.
- 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_69eefacbcc2081909ebf00daa23f1981 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6247832a48190b820e8c0c22ff5db |
completed | May 2, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69f620e0b37481909a280574decbd443 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 9:04 a.m.