Triple
T27693749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tillie Schlaine |
E698228
|
entity |
| Predicate | hasHumanAppearance |
P154256
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Tillie Schlaine, hasHumanAppearance, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHumanAppearance Context triple: [Tillie Schlaine, hasHumanAppearance, true]
-
A.
hasCharacterAppearance
Indicates that a character appears or is visually represented within a given work, scene, or context.
-
B.
hasLifeAppearance
chosen
Indicates that one entity exhibits the visual or observable characteristics typically associated with being alive.
-
C.
hasHumanCharacteristic
Indicates that an entity possesses a trait, quality, or behavior typically associated with humans.
-
D.
hasMediaAppearanceIn
Indicates that an entity appears or is featured as media content within a specified media work, program, or publication.
-
E.
appearanceInImages
Indicates that an entity is visually present or depicted within one or more images.
- 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_69ef590ea74081908f0cd7500d85fa27 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a931748190a637e631a52bbfaa |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 27, 2026, 2:53 p.m.