Triple
T14552460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brushfire Fairytales |
E341451
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Flake |
E341458
|
NE 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: Flake | Statement: [Brushfire Fairytales, hasPart, Flake]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flake Context triple: [Brushfire Fairytales, hasPart, Flake]
-
A.
Flake
chosen
"Flake" is a laid-back, acoustic surf-folk song by Jack Johnson that helped establish his mellow, beach-inspired musical style.
-
B.
Flakes
Flakes is an indie comedy film centered on a quirky New Orleans cereal bar and its eccentric owner and staff.
-
C.
Flaked
Flaked is a Netflix dramedy series co-created by and starring Will Arnett as a self-help guru in Venice, California, whose carefully constructed life begins to unravel.
-
D.
Flucker
Flucker is the surname of Lucy Flucker Knox, the American Revolutionary War-era figure and wife of Continental Army General Henry Knox.
-
E.
Flaemmchen
Flaemmchen is a young, ambitious stenographer and aspiring actress in Vicki Baum’s novel (and its film adaptation) "Grand Hotel," representing the struggles and dreams of working-class women in Weimar-era Berlin.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb2ee34208190bf040a513767c958 |
completed | April 14, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8ab7d698819085fd81d7b6f96317 |
completed | May 8, 2026, 7:03 a.m. |
Created at: April 10, 2026, 1:23 a.m.