Triple
T15204979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lana Condor |
E363365
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Lana Condor |
E363365
|
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: Lana Condor | Statement: [Lana Condor, name, Lana Condor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lana Condor Context triple: [Lana Condor, name, Lana Condor]
-
A.
Lana Condor
chosen
Lana Condor is a Vietnamese-American actress best known for starring as Lara Jean Covey in the Netflix film series "To All the Boys I've Loved Before."
-
B.
Zoey Deutch
Zoey Deutch is an American actress known for her roles in films such as "Before I Fall," "Set It Up," and "Zombieland: Double Tap."
-
C.
Alyvia Alyn Lind
Alyvia Alyn Lind is an American actress best known for her roles in television films and series, including portraying a young Dolly Parton.
-
D.
Kelsey Dohring
Kelsey Dohring is an actress known for playing Chrissy Seaver on the television sitcom "Growing Pains."
-
E.
Mia Kirshner
Mia Kirshner is a Canadian actress known for her dark, nuanced performances in film and television, including her notable role in the crime drama "The Black Dahlia."
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b7964c8190bc8dc3444b94f15e |
completed | April 15, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff677d34748190b5f723b5fd18b3a0 |
completed | May 9, 2026, 4:57 p.m. |
Created at: April 10, 2026, 3:11 a.m.