Triple
T9068870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jets (West Side Story) |
E217310
|
entity |
| Predicate | inUniverseDemographic |
P7875
|
FINISHED |
| Object | teenage boys |
—
|
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: teenage boys | Statement: [Jets (West Side Story), inUniverseDemographic, teenage boys]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inUniverseDemographic Context triple: [Jets (West Side Story), inUniverseDemographic, teenage boys]
-
A.
involvesDemographic
Indicates that an action, event, or entity is related to, affects, or includes a specific demographic group or population segment.
-
B.
demographics
Indicates the relationship of providing or characterizing statistical information about a population’s attributes, such as age, gender, income, or education.
-
C.
hasDemographic
chosen
Indicates that an entity is associated with or characterized by a particular demographic group or attribute.
-
D.
demographicBasis
Indicates that something is determined, classified, or justified based on demographic characteristics such as age, gender, ethnicity, or similar population attributes.
-
E.
demographicsDescriptor
Indicates a descriptive attribute or classification that characterizes the demographic properties of an entity or group.
- 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_69ca83d5a7f48190b16c1e59bd43ede0 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc955ba250819085fa49e0059d06c1 |
completed | April 1, 2026, 3:47 a.m. |
| PD | Predicate disambiguation | batch_69cc65f881248190bfd220bb28a9fb5f |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:11 p.m.