Triple
T8843503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colman Domingo |
E210444
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Zola |
E210446
|
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: Zola | Statement: [Colman Domingo, notableWork, Zola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zola Context triple: [Colman Domingo, notableWork, Zola]
-
A.
Zola
Zola is a French surname most famously borne by Émile Zola, the influential 19th-century novelist and leading figure of literary naturalism.
-
B.
Zola
chosen
Zola is a 2020 dark comedy-drama film based on a viral Twitter thread, following a Detroit waitress on a chaotic road trip into the world of stripping and crime.
-
C.
Zola
Zola is a township neighborhood in Soweto, South Africa, known for its vibrant street culture and significant role in the country’s urban history.
-
D.
Alexandrine Zola
Alexandrine Zola was the wife of French novelist Émile Zola, known for her long and complex marriage to the prominent naturalist writer and her role in managing his household and legacy.
-
E.
Julien
Julien is a given name of French origin commonly used for males in various Francophone and European countries.
- 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_69ca838967bc8190b46c3c80a2887ea4 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc608a73c88190875409fef79ffc8a |
completed | April 1, 2026, 12:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf89ad0a3c8190a2bcf9a106138835 |
completed | April 3, 2026, 9:34 a.m. |
Created at: March 30, 2026, 6:48 p.m.