Triple
T12927562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newborn |
E309282
|
entity |
| Predicate | appearanceDescription |
P311
|
FINISHED |
| Object | pale, fleshy body |
—
|
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: pale, fleshy body | Statement: [Newborn, appearanceDescription, pale, fleshy body]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearanceDescription Context triple: [Newborn, appearanceDescription, pale, fleshy body]
-
A.
appearance
chosen
Indicates how something looks or seems to an observer, including its visible form, condition, or outward impression.
-
B.
hasCharacterAppearance
Indicates that a character appears or is visually represented within a given work, scene, or context.
-
C.
adaptationAppearance
Indicates that one entity appears or is depicted in an adaptation of another entity (such as a work being represented in a derived or reinterpreted version).
-
D.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
E.
mediaAppearanceType
Indicates the specific kind or category of media appearance associated with an entity (e.g., interview, feature, cameo, or performance).
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971ec72a48190aceef10630603d2c |
completed | April 10, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69d96fab4d0881909a7a4d66bab9aa85 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:42 p.m.