Triple
T14184311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tallinn Black Nights Film Festival |
E351534
|
entity |
| Predicate | hasIndustryEvent |
P7624
|
FINISHED |
| Object | co-production market |
—
|
LITERAL 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: co-production market | Statement: [Tallinn Black Nights Film Festival, hasIndustryEvent, co-production market]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIndustryEvent Context triple: [Tallinn Black Nights Film Festival, hasIndustryEvent, co-production market]
-
A.
industryEvent
chosen
Indicates that an event is related to a specific industry, such as a conference, trade show, or professional gathering focused on that industry.
-
B.
hasNotablePersonEvent
Indicates that there exists a significant event in which the person plays a notable or central role.
-
C.
hasPublicEventsIn
Indicates that an entity organizes or holds public events within a specified location or context.
-
D.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
E.
hadEvent
Indicates that an entity experienced, hosted, or was associated with a specific event at some point in time.
- F. None of above.
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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61cc0a848190b660095972b1223b |
completed | April 14, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69de05baed64819096590e5618a3a8ed |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:03 a.m.