Triple
T35142765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sticky Shoes |
E1014739
|
entity |
| Predicate | basedOnCharacterTraitOf |
P37384
|
FINISHED |
| Object | Phoebe Buffay’s eccentric personality |
—
|
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: Phoebe Buffay’s eccentric personality | Statement: [Sticky Shoes, basedOnCharacterTraitOf, Phoebe Buffay’s eccentric personality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnCharacterTraitOf Context triple: [Sticky Shoes, basedOnCharacterTraitOf, Phoebe Buffay’s eccentric personality]
-
A.
associatedCharacterTrait
chosen
Indicates a relationship where a character is linked to, or described by, a particular trait or quality.
-
B.
secondaryCharacterTrait
Indicates that a secondary or supporting character possesses a particular attribute, quality, or personality trait.
-
C.
basedOnCharacterBy
Indicates that one work, adaptation, or portrayal is derived from or inspired by a character created by another entity.
-
D.
protagonistCharacteristic
Indicates that a characteristic, trait, or defining quality is attributed to the protagonist in a narrative or scenario.
-
E.
childCharacterTrait
Indicates that a child possesses or exhibits a particular character trait.
- 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_69f76dda7c108190a2ffd93eb6c341a7 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff1a972bf08190860696ffcd887c0f |
completed | May 9, 2026, 11:29 a.m. |
| PD | Predicate disambiguation | batch_69ff184005d88190bf38283ebc499b28 |
completed | May 9, 2026, 11:19 a.m. |
Created at: May 3, 2026, 4:02 p.m.