Triple
T33383012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Munich (film) |
E854833
|
entity |
| Predicate | originalNetworkOrDistributorRegion |
P204078
|
FINISHED |
| Object | theatrical |
—
|
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: theatrical | Statement: [Munich (film), originalNetworkOrDistributorRegion, theatrical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalNetworkOrDistributorRegion Context triple: [Munich (film), originalNetworkOrDistributorRegion, theatrical]
-
A.
originalPlatformRegion
Indicates the geographic region or market in which a platform was originally launched or made available.
-
B.
distributorCountry
Indicates the country in which the distributor of an item, product, or work is located or operates.
-
C.
countryOrRegionUsed
Indicates that something is used within, or applies to, a specific country or geographic region.
-
D.
hasPrimaryGameRegion
Indicates that an entity is associated with a main or principal geographic region in which a game is released, played, or targeted.
-
E.
networkRegion
Indicates that an entity belongs to, operates within, or is associated with a specific network-defined geographic or logical region.
- F. None of above. chosen
Provenance (4 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_69f3496d54048190a1cb91fdd7caa6ea |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a0317eaf4e88190a6f6419cb4ef7547 |
completed | May 12, 2026, 12:07 p.m. |
| PD | Predicate disambiguation | batch_6a03179da394819095e3d346c3785d74 |
completed | May 12, 2026, 12:05 p.m. |
| PDg | Predicate description generation | batch_6a0317ea3bc08190ac39ccd6b46da625 |
completed | May 12, 2026, 12:07 p.m. |
Created at: May 1, 2026, 1:35 a.m.