Triple
T36929535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snapchat Spotlight |
E913438
|
entity |
| Predicate | algorithmGoal |
P83025
|
FINISHED |
| Object | maximize engagement |
—
|
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: maximize engagement | Statement: [Snapchat Spotlight, algorithmGoal, maximize engagement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: algorithmGoal Context triple: [Snapchat Spotlight, algorithmGoal, maximize engagement]
-
A.
machineGoal
chosen
Indicates that a machine or automated system has a specific objective, target state, or outcome it is intended or programmed to achieve.
-
B.
engineeringGoal
Indicates that an entity has a specific engineering-related objective, target, or desired outcome it is intended to achieve or support.
-
C.
goalState
Indicates the desired or target condition that an entity or system aims to reach or achieve.
-
D.
initialGoal
Indicates that something represents the first or starting objective or target in a sequence of goals.
-
E.
goalStructure
Indicates the overarching objective or intended outcome that organizes and guides the structure of related actions, components, or relationships.
- 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_69f76e896c988190880c130e01303dd4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb55dcf0e881908ff02591266bc58d |
completed | May 6, 2026, 2:53 p.m. |
| PD | Predicate disambiguation | batch_69f7cf79ddb08190a083405cccc14137 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:13 p.m.