Triple
T2436682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Polanski |
E52976
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object | Tess |
E265925
|
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: Tess | Statement: [Roman Polanski, directed, Tess]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tess Context triple: [Roman Polanski, directed, Tess]
-
A.
Tess
chosen
Tess is a 1979 period drama film directed by Roman Polanski, adapted from Thomas Hardy’s novel "Tess of the d'Urbervilles."
-
B.
Tess
Tess is a central character in the musical film "Burlesque," serving as the tough but caring owner and manager of the struggling burlesque club.
-
C.
The Farmer’s Daughter
The Farmer’s Daughter is a 1947 American romantic comedy film starring Loretta Young as a Swedish-American farm girl who becomes involved in politics.
-
D.
Adam Bede
Adam Bede is a 1859 realist novel by George Eliot that portrays rural English life and moral dilemmas through the story of a principled carpenter and those around him.
-
E.
Bathsheba
Bathsheba is a prominent biblical figure known as the wife of King David and the mother of King Solomon.
- 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_69ab4959bcc0819083246f9fb10439e3 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc9f342e88190a430b02842ded418 |
completed | March 7, 2026, 6:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef0ad31b8819084813b65b46bc9fc |
completed | March 9, 2026, 4:09 p.m. |
Created at: March 6, 2026, 9:43 p.m.