Triple
T32294213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manny Garcia |
E825043
|
entity |
| Predicate | showTargetAudience |
P155271
|
FINISHED |
| Object | preschool children |
—
|
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: preschool children | Statement: [Manny Garcia, showTargetAudience, preschool children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: showTargetAudience Context triple: [Manny Garcia, showTargetAudience, preschool children]
-
A.
targetMarket
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
-
B.
targetAudienceTheme
chosen
Indicates the thematic focus or type of audience that a work, message, or product is specifically intended to appeal to or address.
-
C.
resultForAudience
Indicates that something is produced or presented specifically to achieve an effect or outcome for a particular audience.
-
D.
relatesToAudience
Indicates a general relationship or relevance between something and a particular audience or group of recipients.
-
E.
targetAudienceKnowledge
Indicates the level or type of prior knowledge that the intended audience is expected to have.
- 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_69f349101b788190b4f14884dc7d1ed2 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bd38959c8190ab96268f1c8016e7 |
completed | May 3, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69f6b632cf788190a3d0c08cd026b84b |
completed | May 3, 2026, 2:42 a.m. |
Created at: May 1, 2026, 12:44 a.m.