Triple
T9284026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German Film Award |
E223139
|
entity |
| Predicate | hasTrophyName |
P13950
|
FINISHED |
| Object | Lola |
E412873
|
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: Lola | Statement: [German Film Award, hasTrophyName, Lola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lola Context triple: [German Film Award, hasTrophyName, Lola]
-
A.
Lola
Lola is a fictional character portrayed by British actor Chiwetel Ejiofor.
-
B.
Lola
chosen
Lola is a 1981 West German drama film directed by Rainer Werner Fassbinder, in which Armin Mueller-Stahl plays a prominent role in a story set in postwar Germany.
-
C.
Lola
Lola is the charismatic drag queen and performer who serves as the central catalyst for change in the musical and film "Kinky Boots."
-
D.
Lola
Lola is a 1961 French New Wave film directed by Jacques Demy, featuring Corinne Marchand in the title role as a cabaret singer in the port city of Nantes.
-
E.
Lola Van Wagenen
Lola Van Wagenen is an American historian, activist, and co-founder of the consumer education organization Consumer Action Now, known also for her longtime marriage to actor Robert Redford.
- 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_69ca842123588190b3f2e1a69037d141 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd081e72988190917f425e64631837 |
completed | April 1, 2026, 11:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0c75b9d308190918f181e13df955a |
completed | April 4, 2026, 8:10 a.m. |
Created at: March 30, 2026, 7:34 p.m.