Triple
T17404669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mudbound |
E423180
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object | Hillary Jordan |
—
|
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: Hillary Jordan | Statement: [Mudbound, author, Hillary Jordan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hillary Jordan Context triple: [Mudbound, author, Hillary Jordan]
-
A.
Hillary Jordan
chosen
Hillary Jordan is an American novelist best known for her award-winning debut novel "Mudbound," a historical drama exploring race, family, and hardship in the Jim Crow-era Mississippi Delta.
-
B.
Anna Jordan
Anna Jordan is a musician and composer known for creating music for the film "Breakfast on Pluto."
-
C.
Nessa Jenkins
Nessa Jenkins is a deadpan, no-nonsense Welsh character from the British sitcom "Gavin & Stacey," known for her eccentric stories and iconic catchphrases.
-
D.
Roslyn Jordan
Roslyn Jordan is one of the daughters of Deloris Jordan and a member of the family of basketball legend Michael Jordan.
-
E.
Rachel Scott
Rachel Scott was a 17-year-old student, aspiring writer, and the first person killed in the Columbine High School shooting, later remembered for her journals and advocacy for kindness.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43b068248819088871d79f8a38f30 |
completed | April 19, 2026, 2:16 a.m. |
Created at: April 10, 2026, 5:45 a.m.