Triple
T34061807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lizard Girl |
E873509
|
entity |
| Predicate | bodyModificationPurpose |
P167840
|
FINISHED |
| Object | to resemble a lizard |
—
|
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: to resemble a lizard | Statement: [Lizard Girl, bodyModificationPurpose, to resemble a lizard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bodyModificationPurpose Context triple: [Lizard Girl, bodyModificationPurpose, to resemble a lizard]
-
A.
bodyModificationReason
chosen
Indicates the reason or motivation behind a particular body modification performed on an entity.
-
B.
bodyModificationTheme
Indicates that the relationship or action involves themes of altering, modifying, or transforming bodies or physical forms.
-
C.
bodyTreatment
Indicates a treatment or therapeutic procedure that is applied to a person's body.
-
D.
bodyTransformation
Indicates a change in an entity’s physical form, structure, or appearance into a different bodily state.
-
E.
bodyArt
Indicates that one entity has body art (such as tattoos, piercings, or similar modifications) applied to or present on 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_69f349a4af208190afa14888f9c9fb9d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70fb4f18c819099ef6d9177b7d205 |
completed | May 3, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f70f3a54d481909ba6bdda3647b761 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:52 a.m.