Triple
T15339114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kellan Christopher Lutz |
E366743
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Kellan Christopher Lutz |
E366743
|
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: Kellan Christopher Lutz | Statement: [Kellan Christopher Lutz, name, Kellan Christopher Lutz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kellan Christopher Lutz Context triple: [Kellan Christopher Lutz, name, Kellan Christopher Lutz]
-
A.
Kellan Christopher Lutz
chosen
Kellan Christopher Lutz is an American actor and model best known for his role as Emmett Cullen in the "Twilight" film series.
-
B.
Kaylan Cloyd
Kaylan Cloyd is an individual associated with the organization or group known as Acceptance.
-
C.
Aidan Keller
Aidan Keller is the young, psychically sensitive boy central to the plot of the horror film "The Ring."
-
D.
Kristopher Nathan Humphries
Kristopher Nathan Humphries is an American former professional basketball player best known for his NBA career and brief, highly publicized marriage to Kim Kardashian.
-
E.
Jordan Kerner
Jordan Kerner is an American film and television producer known for projects such as "Less Than Zero" and the live-action "The Smurfs" films.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e12eb7c8190944a260aa1aa9156 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01f2ee9c819080fce24ed13a07c7 |
completed | May 9, 2026, 9:44 a.m. |
Created at: April 10, 2026, 3:17 a.m.