Triple
T15576679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Top Girls |
E374386
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Marlene |
E1164670
|
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: Marlene | Statement: [Top Girls, character, Marlene]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marlene Context triple: [Top Girls, character, Marlene]
-
A.
Marlene
Marlene is an energetic and friendly otter who appears as a main supporting character in the animated series "The Penguins of Madagascar."
-
B.
Marlene
chosen
Marlene is the ambitious, career-driven protagonist of Caryl Churchill’s play "Top Girls," whose life embodies the tensions between feminism, success, and personal sacrifice.
-
C.
Marlene
Marlene is a German biographical film directed by Joseph Vilsmaier about the life and career of actress and singer Marlene Dietrich.
-
D.
Audrey
Audrey is the sweet but beleaguered love interest and florist’s assistant in the horror-comedy musical "Little Shop of Horrors."
-
E.
Audrey
Audrey is a simple, rustic shepherdess who serves as a comic character in William Shakespeare’s pastoral comedy "As You Like It."
- 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e22c89081909b1ec0cd36a1ef45 |
completed | April 16, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56c3efb48190ad94d9d326c6c2c0 |
completed | May 9, 2026, 3:46 p.m. |
Created at: April 10, 2026, 4:10 a.m.