Triple
T3233296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kendall Jenner |
E67792
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Kendall |
E230734
|
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: Kendall | Statement: [Kendall Jenner, givenName, Kendall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kendall Context triple: [Kendall Jenner, givenName, Kendall]
-
A.
Kendall
chosen
Kendall is a unisex given name of English origin commonly used in the United States and other English-speaking countries.
-
B.
Kendall
Kendall is a neighborhood in Cambridge, Massachusetts, known for its proximity to MIT and its concentration of technology companies and research institutions.
-
C.
Kendall Nesbitt
Kendall Nesbitt is a fictional character from the musical "Lady in the Dark," typically portrayed as a sophisticated romantic interest entangled in the protagonist's emotional and psychological journey.
-
D.
Kendall Vanhook Bumpass
Kendall Vanhook Bumpass was a 19th-century cowboy and guide whose accidental injury in Lassen Peak’s geothermal area led to the site being named Bumpass Hell in his memory.
-
E.
Carley Knox
Carley Knox is a sports executive best known for her leadership role in the WNBA’s Minnesota Lynx organization.
- 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_69ad858d27348190abb61c280b4c86a9 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaedb718c8190aae12f763033713a |
completed | March 8, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2773b494c8190a2c0c5042e8eaa55 |
completed | March 12, 2026, 8:20 a.m. |
Created at: March 8, 2026, 3:08 p.m.