Triple
T35272249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brooklyn, New York (fictionalized) |
E1018699
|
entity |
| Predicate | portraysDemographic |
P58038
|
FINISHED |
| Object | Black upper-middle-class family |
—
|
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: Black upper-middle-class family | Statement: [Brooklyn, New York (fictionalized), portraysDemographic, Black upper-middle-class family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysDemographic Context triple: [Brooklyn, New York (fictionalized), portraysDemographic, Black upper-middle-class family]
-
A.
involvesDemographic
chosen
Indicates that an action, event, or entity is related to, affects, or includes a specific demographic group or population segment.
-
B.
hasDemographic
Indicates that an entity is associated with or characterized by a particular demographic group or attribute.
-
C.
demographicsDescriptor
Indicates a descriptive attribute or classification that characterizes the demographic properties of an entity or group.
-
D.
portraysAgeGroup
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
E.
demographicsCharacteristic
Indicates that one entity serves as a demographic attribute or characteristic (such as age, gender, ethnicity, etc.) that describes or classifies another entity.
- 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_69f76de5c4788190896ad598ae7d6bc6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff41645c548190b7cb4e53079b93ef |
completed | May 9, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_69ff410aa33c8190869ba769ac2a93ce |
completed | May 9, 2026, 2:13 p.m. |
Created at: May 3, 2026, 4:02 p.m.