Triple
T14404097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Time Lady |
E357151
|
entity |
| Predicate | canChangePersonality |
P102538
|
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: [Time Lady, canChangePersonality, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canChangePersonality Context triple: [Time Lady, canChangePersonality, true]
-
A.
hasMainPersonality
Indicates that one entity possesses or is characterized by a primary or dominant personality associated with another entity.
-
B.
characterRoleSwap
Indicates a relationship where two characters exchange or assume each other’s narrative roles or functions within a story or scenario.
-
C.
dynamicCharacter
chosen
Indicates that a character undergoes significant internal change or development over the course of a narrative.
-
D.
featuresNumberOfPersonalities
Indicates that an entity is characterized by or contains a specified number of distinct personalities.
-
E.
hasPersona
Indicates that an entity possesses or is associated with a particular persona, role, or character profile.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90860ae481908e175decda8624d5 |
completed | April 14, 2026, 7:07 p.m. |
| PD | Predicate disambiguation | batch_69de2aa024c48190805df6a9d63deb10 |
completed | April 14, 2026, 11:53 a.m. |
Created at: April 10, 2026, 1:17 a.m.