Triple
T2236275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katia Mann |
E49287
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Monika Mann |
E42635
|
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: Monika Mann | Statement: [Katia Mann, child, Monika Mann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monika Mann Context triple: [Katia Mann, child, Monika Mann]
-
A.
Monika Mann
chosen
Monika Mann was a German writer and essayist, best known as one of the literary Nobel laureate Thomas Mann’s daughters and a member of the prominent Mann family of intellectuals.
-
B.
Loveleen Tandan
Loveleen Tandan is an Indian film director and casting director best known for her co-directing work on the Academy Award–winning film "Slumdog Millionaire."
-
C.
Shivani Ghai
Shivani Ghai is a British actress known for her work in television, film, and theatre, including roles in series such as "EastEnders" and "Dominion."
-
D.
Marianne Mithun
Marianne Mithun is an American linguist renowned for her extensive work on Native American languages, language typology, and the documentation of endangered languages.
-
E.
Palak Patel
Palak Patel is a film producer known for working on major Hollywood fantasy and action films, including "Snow White and the Huntsman."
- 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_69a88aa84bdc819086df50e9c20b301e |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc093ba0c819091df09a0e018fce1 |
completed | March 7, 2026, 6:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6b08c5248190924a28f4c1bd0e2c |
completed | March 9, 2026, 6:39 a.m. |
Created at: March 4, 2026, 7:47 p.m.