Triple
T15965605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stop (Mean Girls song) |
E387181
|
entity |
| Predicate | intendedEffectOnCharacters |
P36788
|
FINISHED |
| Object | encourage reflection |
—
|
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: encourage reflection | Statement: [Stop (Mean Girls song), intendedEffectOnCharacters, encourage reflection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intendedEffectOnCharacters Context triple: [Stop (Mean Girls song), intendedEffectOnCharacters, encourage reflection]
-
A.
influencesCharacter
chosen
Indicates that one entity affects, shapes, or alters the traits, behavior, or development of another entity’s character.
-
B.
effectOnOthers
Indicates the impact or influence that one entity’s actions, presence, or state has on other entities.
-
C.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
D.
plotCharacter
Indicates a relationship where a character plays a role or participates in the narrative plot of a story or work.
-
E.
predictedEffect
Indicates that one entity is expected to cause, influence, or result in a particular outcome or consequence for 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142d6fb588190b4176eab4bbae774 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:54 a.m.