Triple
T17201594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Predators (2010 film) |
E417486
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Noland |
E535671
|
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: Noland | Statement: [Predators (2010 film), mainCharacter, Noland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noland Context triple: [Predators (2010 film), mainCharacter, Noland]
-
A.
Noland
chosen
Noland is a surname most notably associated with Kenneth Noland, an influential American abstract painter linked to the Color Field movement.
-
B.
Boland
Boland is a rugby union region in South Africa whose teams and players are partly represented at the professional level by the Stormers franchise.
-
C.
Pangborn
Pangborn is a surname most notably associated with American character actor Franklin Pangborn, known for his comedic roles in early 20th-century films.
-
D.
Nelsan
Nelsan is the given name of Nelsan Ellis, an American actor best known for his role as Lafayette Reynolds on the television series "True Blood."
-
E.
Nylund
Nylund is a Scandinavian-origin surname most widely recognized through the fictional character Rose Nylund from the television series "The Golden Girls."
- 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42db014b08190b88a5001e9f7811b |
completed | April 19, 2026, 1:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a015fda06788190882aef1a57356e41 |
completed | May 11, 2026, 4:49 a.m. |
Created at: April 10, 2026, 5:38 a.m.