Triple
T30569076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sky Masterson |
E778071
|
entity |
| Predicate | relationshipDynamicWithSarahBrown |
P204102
|
FINISHED |
| Object | opposites attract |
—
|
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: opposites attract | Statement: [Sky Masterson, relationshipDynamicWithSarahBrown, opposites attract]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipDynamicWithSarahBrown Context triple: [Sky Masterson, relationshipDynamicWithSarahBrown, opposites attract]
-
A.
relationshipToSarahLeary
Indicates the specific type of relationship or connection an entity has to Sarah Leary.
-
B.
relationshipDynamicWithBrad
Indicates a relationship whose nature, intensity, or status changes over time in connection with Brad.
-
C.
relationshipToAlice
Indicates the specific type of relationship or connection that an entity has with Alice.
-
D.
relationshipWithEmmyBrown
Indicates that there exists some form of personal, professional, or social relationship involving Emmy Brown and another entity.
-
E.
relationshipToMichelle
Indicates the specific type of relationship or connection that an entity has to Michelle.
- F. None of above. chosen
Provenance (4 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_69f2249f8c148190ae7eb3912cde112a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a0324c2d618819093f7e6424b0f5baf |
completed | May 12, 2026, 1:01 p.m. |
| PD | Predicate disambiguation | batch_6a0324292e588190b37d0c3016ea2062 |
completed | May 12, 2026, 12:59 p.m. |
| PDg | Predicate description generation | batch_6a0324c1f89881909fc713e93e9c5f1c |
completed | May 12, 2026, 1:01 p.m. |
Created at: April 29, 2026, 8:21 p.m.