Triple
T14869283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ZFF Summit |
E349700
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | ZFF Summit |
E349700
|
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: ZFF Summit | Statement: [ZFF Summit, name, ZFF Summit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ZFF Summit Context triple: [ZFF Summit, name, ZFF Summit]
-
A.
ZFF Summit
chosen
ZFF Summit is a key industry conference and discussion platform held during the Zurich Film Festival, bringing together filmmakers, executives, and thought leaders to explore current issues and trends in cinema and entertainment.
-
B.
ZFF Masters
ZFF Masters is a Zurich Film Festival program featuring in-depth masterclasses and conversations with prominent filmmakers and industry professionals.
-
C.
ZFF
ZFF is the abbreviation for the Zurich Film Festival, an annual international film festival held in Zurich, Switzerland.
-
D.
ZFF Industry
ZFF Industry is the Zurich Film Festival’s professional platform that hosts industry events, networking opportunities, and business initiatives for film professionals.
-
E.
MWFF
MWFF is the abbreviation for the Montreal World Film Festival, an international film festival held annually in Montreal, Canada.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5776b848190bfe3a06ff261dc31 |
completed | April 15, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe651067cc8190b9c218ef1f802762 |
completed | May 8, 2026, 10:34 p.m. |
Created at: April 10, 2026, 1:55 a.m.