Triple
T10334781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Film Studio |
E242971
|
entity |
| Predicate | hasBacklotType |
P7951
|
FINISHED |
| Object | urban street backlot |
—
|
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: urban street backlot | Statement: [Shanghai Film Studio, hasBacklotType, urban street backlot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBacklotType Context triple: [Shanghai Film Studio, hasBacklotType, urban street backlot]
-
A.
hasBacklot
chosen
Indicates that one entity possesses or includes a backlot area associated with it.
-
B.
hasPorch
Indicates that one entity (typically a building or residence) includes or is equipped with a porch as part of its structure.
-
C.
hasOutdoorSpaceType
Indicates the specific kind of outdoor area associated with an entity, such as a balcony, terrace, garden, or patio.
-
D.
hasStandingArea
Indicates that an entity includes or provides a designated area where people can stand.
-
E.
hasBalcony
Indicates that a building or dwelling includes a balcony as part of its structure or features.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e91fdb2081909866c6ecf417d75a |
completed | April 7, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69d4df9dc3208190bf1bd106f44f6202 |
completed | April 7, 2026, 10:42 a.m. |
Created at: April 6, 2026, 11:53 a.m.