Triple
T15339115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kellan Christopher Lutz |
E366743
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Kellan |
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 | Statement: [Kellan Christopher Lutz, givenName, Kellan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kellan Context triple: [Kellan Christopher Lutz, givenName, Kellan]
-
A.
Kellen
Kellen is a masculine given name most notably associated with former NFL tight end and Hall of Famer Kellen Winslow.
-
B.
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.
-
C.
Kelli
Kelli is a feminine given name, typically considered a variant spelling of Kelly.
-
D.
Kiley
Kiley is a given name used for people of any gender, often considered a variant spelling of names like Kylie or Kylee.
-
E.
Kelan
Kelan is a masculine given name used in various English-speaking countries, sometimes considered a modern variant of names like Kellen or Keelan.
- 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_69ff0b41f130819082ea69ea535468ce |
completed | May 9, 2026, 10:24 a.m. |
Created at: April 10, 2026, 3:17 a.m.