Triple
T3379340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Fontana |
E71142
|
entity |
| Predicate | wroteFor |
P1996
|
FINISHED |
| Object | Oz |
E101318
|
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: Oz | Statement: [Tom Fontana, wroteFor, Oz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oz Context triple: [Tom Fontana, wroteFor, Oz]
-
A.
Oz
chosen
Oz is a gritty HBO drama series set in a maximum-security prison, known for its dark, realistic portrayal of inmate life and institutional violence.
-
B.
OZ
OZ is the IATA airline designator assigned to Asiana Airlines, a major South Korean carrier based in Seoul.
-
C.
Oz, the Great and Horrible
Oz, the Great and Horrible is the imposing yet ultimately humbug wizard who rules the Emerald City in L. Frank Baum’s classic novel "The Wonderful Wizard of Oz."
-
D.
Land of Oz
The Land of Oz is a fantastical, magical country from L. Frank Baum’s children’s book series, best known as the colorful, whimsical world visited by Dorothy and her friends.
-
E.
Return to Oz
Return to Oz is a 1985 dark fantasy film that serves as an unofficial sequel to The Wizard of Oz, blending elements from several of L. Frank Baum’s Oz books into a darker, more surreal adventure.
- 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_69ad85a7f80c8190a05e43013f298942 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2ec38d88190be8c824daeca5ab6 |
completed | March 8, 2026, 5:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b35460b4a081908f05bf786cc9bcd3 |
completed | March 13, 2026, 12:03 a.m. |
Created at: March 8, 2026, 3:14 p.m.