Triple
T3792178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julie Gillis |
E89677
|
entity |
| Predicate | fictionalUniverse |
P3758
|
FINISHED |
| Object | The Tender Trap universe |
E3521
|
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: The Tender Trap universe | Statement: [Julie Gillis, fictionalUniverse, The Tender Trap universe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Tender Trap universe Context triple: [Julie Gillis, fictionalUniverse, The Tender Trap universe]
-
A.
The Tender Trap
chosen
The Tender Trap is a 1955 romantic comedy film starring Frank Sinatra and Debbie Reynolds, adapted from the Broadway play of the same name.
-
B.
The Trap
"The Trap" is a horror novel by Tabitha King that delves into psychological terror and the darker sides of human relationships in a small-town setting.
-
C.
Trife
Trife is a rapper best known as a member of the Brooklyn hip hop collective Junior M.A.F.I.A.
-
D.
The Steel Trap
The Steel Trap is a 1952 American crime thriller film starring Joseph Cotten as a bank employee who devises a plan to steal money and flee the country.
-
E.
The Land of Take-What-You-Want
The Land of Take-What-You-Want is a magical realm in Enid Blyton’s Faraway Tree stories where visitors can freely help themselves to any object or treat they desire.
- 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_69aed9597d6881909b6ee3b9de859223 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee769d68081908dcdd3d232dbb61c |
completed | March 9, 2026, 3:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f058f03881909aded87e7a74849f |
completed | March 14, 2026, 5:21 a.m. |
Created at: March 9, 2026, 3:15 p.m.