Triple
T12576674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julie Schumann |
E300224
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Julie |
E124624
|
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: Julie | Statement: [Julie Schumann, givenName, Julie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julie Context triple: [Julie Schumann, givenName, Julie]
-
A.
Julie
chosen
Julie is a feminine given name of Latin origin, commonly used in many Western countries.
-
B.
Janet
Janet is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
-
C.
Marnie
Marnie is a 1964 psychological thriller film directed by Alfred Hitchcock, starring Tippi Hedren and Sean Connery, about a troubled woman with a mysterious past and compulsive thieving.
-
D.
Margo
Margo is the responsible and intelligent eldest of Gru’s three adopted daughters in the Despicable Me franchise.
-
E.
Margo
Margo is a feminine given name commonly used in English-speaking countries, often considered a variant of Margot or Margaret.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954a73c148190bba8f16b1232fd46 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65597dc70819089ddc1794e9bd1b7 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 9, 2026, 4:51 p.m.