Triple
T3438000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Askival |
E72500
|
entity |
| Predicate | listing |
P1278
|
FINISHED |
| Object | Marilyn |
E35887
|
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: Marilyn | Statement: [Askival, listing, Marilyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marilyn Context triple: [Askival, listing, Marilyn]
-
A.
Marilyn
chosen
A Marilyn is a type of British hill or mountain classified by having a prominence of at least 150 meters, regardless of its absolute height.
-
B.
Marlene
Marlene is a German biographical film directed by Joseph Vilsmaier about the life and career of actress and singer Marlene Dietrich.
-
C.
Marilyn Monroe
Marilyn Monroe was an iconic American actress, model, and sex symbol of the mid-20th century, renowned for her comedic roles, glamorous image, and enduring cultural legacy.
-
D.
Gloria
Gloria is a 1980 American crime drama film written and directed by John Cassavetes, starring Gena Rowlands as a tough ex-mobster’s girlfriend protecting a young boy from gangsters.
-
E.
Gloria
Gloria is a joyful hymn of praise in Christian liturgy, traditionally sung during major celebrations such as the Easter Vigil.
- 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_69ad85af50288190a854b76653deee6f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9f575cc8190866929b1e8930143 |
completed | March 8, 2026, 6:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b367f6bb90819084055d9d001430fd |
completed | March 13, 2026, 1:27 a.m. |
Created at: March 8, 2026, 3:16 p.m.