Triple
T35162667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beau Langdon |
E1015309
|
entity |
| Predicate | bondWithCharacter |
P68132
|
FINISHED |
| Object | Addie Langdon |
—
|
NE NERFINISHED |
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: Addie Langdon | Statement: [Beau Langdon, bondWithCharacter, Addie Langdon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bondWithCharacter Context triple: [Beau Langdon, bondWithCharacter, Addie Langdon]
-
A.
bondedWith
chosen
Indicates that two entities are joined by a strong, enduring connection or attachment, whether emotional, social, or structural.
-
B.
gắnVớiNhânVật
Indicates a relationship in which something is associated, connected, or tied to a particular character or person.
-
C.
brandCharacter
Indicates that one entity serves as a brand character or mascot representing another entity (typically a brand or product).
-
D.
associatedWithCharacterRole
Indicates that one entity has a connection or linkage to a specific character role played or held by another entity.
-
E.
basedOnCharacterBy
Indicates that one work, adaptation, or portrayal is derived from or inspired by a character created by 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_69f76ddbfde081908bffc91572368289 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78d2c63408190aa9a1bfc18a3e021 |
completed | May 3, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69f78b9106008190930b3b3675b737d6 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:02 p.m.