Triple
T10985652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Therese Giehse |
E259622
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Therese |
E195946
|
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: Therese | Statement: [Therese Giehse, givenName, Therese]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Therese Context triple: [Therese Giehse, givenName, Therese]
-
A.
Therese
chosen
Therese is a feminine given name of French origin, commonly associated with Christian saints and used in various European cultures.
-
B.
Renée
Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
-
C.
Madelaine
Madelaine is a character in the Danish crime thriller film "The Salvation."
-
D.
Estelle
Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
-
E.
Therese Gift
Therese Gift, better known by her stage name Therese Giehse, was a prominent German actress renowned for her work in theatre and film, particularly in the mid-20th century.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d787b2e4a88190a81504eee77e2298 |
completed | April 9, 2026, 11:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e374526d54819085a0fb0d62f7a581 |
completed | April 18, 2026, 12:08 p.m. |
Created at: April 8, 2026, 9:24 p.m.