Triple
T8999699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marked Woman |
E215010
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Lola Lane |
E292221
|
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: Lola Lane | Statement: [Marked Woman, starring, Lola Lane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lola Lane Context triple: [Marked Woman, starring, Lola Lane]
-
A.
Lola Lane
chosen
Lola Lane was an American film actress best known as one of the Lane Sisters, who appeared in numerous Hollywood productions during the 1930s and 1940s.
-
B.
Lola Stone
Lola Stone is the sadistic, prom-obsessed teenage antagonist from the Australian horror film "The Loved Ones."
-
C.
Lanie Parish
Lanie Parish is a sharp-witted medical examiner and close friend of Kate Beckett on the crime-comedy TV series "Castle."
-
D.
Natalie Lane
Natalie Lane is a teenage girl character from the 1960s sitcom "The Patty Duke Show," known as Patty Lane’s more serious and studious identical cousin.
-
E.
Darlene
Darlene is a fictional character portrayed by actress Dominique Fishback, known from her work in film and television dramas.
- 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc68e3b1f48190bbeafbce363fff53 |
completed | April 1, 2026, 12:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0d987dc81908f1d74f390f18a9c |
completed | April 3, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:05 p.m.