Triple
T35015001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hot to the Touch |
E1010029
|
entity |
| Predicate | hasSeriesTargetDemographic |
P129256
|
FINISHED |
| Object | children and teens |
—
|
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: children and teens | Statement: [Hot to the Touch, hasSeriesTargetDemographic, children and teens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeriesTargetDemographic Context triple: [Hot to the Touch, hasSeriesTargetDemographic, children and teens]
-
A.
intendedAudienceOfSeries
chosen
Indicates that a particular audience is the primary target or intended recipient of a given series.
-
B.
targetAudienceOfFilms
Indicates the group of people or demographic segment that a particular film is primarily intended or designed to appeal to.
-
C.
typicalAudience
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
-
D.
hasEthnicTarget
Indicates that an action, statement, or event is directed toward or targets a specific ethnic group.
-
E.
targetAudienceAtRelease
Indicates the group of people a work, product, or content was primarily intended for at the time it was first released.
- 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_69f76dcc3ac8819096a3ed52f5fa2523 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fffbb5d0188190b6d168de8626ff68 |
completed | May 10, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69fffa3bc1208190a277961385a4789f |
completed | May 10, 2026, 3:23 a.m. |
Created at: May 3, 2026, 4:01 p.m.