Triple
T29002642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Red-Haired Girl |
E736344
|
entity |
| Predicate | relationshipToCharlieBrown |
P38921
|
FINISHED |
| Object | object of affection |
—
|
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: object of affection | Statement: [Little Red-Haired Girl, relationshipToCharlieBrown, object of affection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToCharlieBrown Context triple: [Little Red-Haired Girl, relationshipToCharlieBrown, object of affection]
-
A.
relationshipToBelcherChildren
Indicates the specific familial or caretaking relationship an entity has to the Belcher children.
-
B.
relationshipToPeppermintPatty
Indicates the specific type of personal or social relationship an entity has with Peppermint Patty.
-
C.
relationshipToBobBelcher
Indicates the specific familial, social, or professional relationship that one entity has to Bob Belcher.
-
D.
relationshipToHuckFinn
Indicates the specific type of personal or social relationship an entity has to Huck Finn.
-
E.
relationshipToCharacter
chosen
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
- 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_69f077eb81e88190ad9ff62cbb9f555e |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_6a00af6b3a948190a92813c13384c304 |
completed | May 10, 2026, 4:16 p.m. |
| PD | Predicate disambiguation | batch_6a00aec35610819085dd5137715a4228 |
completed | May 10, 2026, 4:13 p.m. |
Created at: April 28, 2026, 9:35 a.m.