Triple
T16105490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Perfect World |
E390727
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | T.J. Lowther |
E755730
|
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: T.J. Lowther | Statement: [A Perfect World, starring, T.J. Lowther]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T.J. Lowther Context triple: [A Perfect World, starring, T.J. Lowther]
-
A.
T.J. Lowther
chosen
T.J. Lowther is an American former child actor best known for his roles in films and television during the 1990s.
-
B.
T. J. Lavin
T. J. Lavin is an American BMX rider and television personality best known as the longtime host of MTV’s reality competition series "The Challenge."
-
C.
T. J. Tynan
T. J. Tynan is an American professional ice hockey forward known as one of the AHL’s elite playmakers and a multiple-time league MVP.
-
D.
T.J. Hanniger
T.J. Hanniger is a central protagonist in the 1981 Canadian slasher film "My Bloody Valentine," known for returning to his mining hometown as a love-triangle and potential-suspect figure amid a series of brutal murders.
-
E.
TJ Wright
TJ Wright is an actor best known for his role in the film adaptation of Angie Thomas's novel "The Hate U Give."
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff6b91a48190a04648d4cad2c4b1 |
completed | April 17, 2026, 9:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeba1e4c08190a90f5102e0038056 |
completed | May 10, 2026, 2:21 a.m. |
Created at: April 10, 2026, 5 a.m.