Triple
T18661297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melissa Stribling |
E456202
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Melissa Stribling |
—
|
NE NERFINISHED |
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: Melissa Stribling | Statement: [Melissa Stribling, name, Melissa Stribling]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melissa Stribling Context triple: [Melissa Stribling, name, Melissa Stribling]
-
A.
Melissa Stribling
chosen
Melissa Stribling was a British actress best known for her role in the classic 1958 Hammer horror film "Horror of Dracula."
-
B.
Kristin Yancey
Kristin Yancey is a fictional character from the American television sitcom "Kristin."
-
C.
Molly Smith
Molly Smith is a daughter of FedEx founder and CEO Frederick W. Smith.
-
D.
Molly Smith
Molly Smith is an American film producer known for her work on acclaimed movies such as the crime thriller "Sicario."
-
E.
Kate Burroughs
Kate Burroughs is the central protagonist of the film "The Four Seasons," around whom the story’s relationships and events revolve.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38f72b4819090a935175d9ca8af |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5508a30248190abdb51e345168849 |
completed | April 19, 2026, 10 p.m. |
Created at: April 10, 2026, 11:48 a.m.