Triple
T7263233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marnie Michaels |
E159706
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | Lena Dunham |
E151336
|
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: Lena Dunham | Statement: [Marnie Michaels, creator, Lena Dunham]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lena Dunham Context triple: [Marnie Michaels, creator, Lena Dunham]
-
A.
Lena Dunham
chosen
Lena Dunham is an American writer, director, and actress best known for creating and starring in the HBO series "Girls," which explored the lives of young women in New York City.
-
B.
Rachel Bloom
Rachel Bloom is an American actress, comedian, writer, and singer best known for co-creating and starring in the musical comedy television series "Crazy Ex-Girlfriend."
-
C.
Tavi Gevinson
Tavi Gevinson is an American writer, editor, and actress who first gained prominence as a teenage fashion blogger and founder of the online magazine Rookie.
-
D.
Annalee Newman
Annalee Newman was the wife of influential American abstract expressionist painter Barnett Newman and an important steward of his artistic legacy.
-
E.
Ari Wegner
Ari Wegner is an acclaimed Australian cinematographer known for her visually striking work on films such as "The Power of the Dog."
- 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_69c68838f9948190875fd60b2351230c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eac9fab88190881ab9e1cd94cdc1 |
completed | March 27, 2026, 8:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7d3c3bfb48190877ba03ab0851a68 |
completed | March 28, 2026, 1:12 p.m. |
Created at: March 27, 2026, 2:57 p.m.