Triple
T35422410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rex |
E1023828
|
entity |
| Predicate | hasAppearanceTrait |
P31173
|
FINISHED |
| Object | Large head |
—
|
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: Large head | Statement: [Rex, hasAppearanceTrait, Large head]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAppearanceTrait Context triple: [Rex, hasAppearanceTrait, Large head]
-
A.
hasCharacterAppearance
Indicates that a character appears or is visually represented within a given work, scene, or context.
-
B.
hasHumanCharacteristic
Indicates that an entity possesses a trait, quality, or behavior typically associated with humans.
-
C.
hasPhysicalFeature
chosen
Indicates that one entity possesses or exhibits a specific physical characteristic or feature of another entity.
-
D.
appearanceIncludes
Indicates that one entity’s visual or outward characteristics contain, feature, or incorporate those of another entity.
-
E.
hasMediaAppearanceIn
Indicates that an entity appears or is featured as media content within a specified media work, program, or publication.
- 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_69f76df6704081909900c60be10d5849 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fde9fc184c8190bebef35df0e76076 |
completed | May 8, 2026, 1:49 p.m. |
| PD | Predicate disambiguation | batch_69fde6e5beb4819094945a695e961d88 |
completed | May 8, 2026, 1:36 p.m. |
Created at: May 3, 2026, 4:03 p.m.