Triple
T6135006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eve Harrington |
E136810
|
entity |
| Predicate | truePersona |
P61233
|
FINISHED |
| Object | ruthless social climber |
—
|
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: ruthless social climber | Statement: [Eve Harrington, truePersona, ruthless social climber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: truePersona Context triple: [Eve Harrington, truePersona, ruthless social climber]
-
A.
hasPersona
chosen
Indicates that an entity possesses or is associated with a particular persona, role, or character profile.
-
B.
realName
Indicates that one entity is the actual, full, or birth name of another entity, which may be known by an alias, nickname, or alternate identity.
-
C.
namedAfterFictionalCharacter
Indicates that one entity has been given its name in honor of, or derived from, a fictional character.
-
D.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
E.
basedOnRealPersonFor
Indicates that one entity is created, modeled, or inspired using a specific real person as its basis.
- 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_69c008a179388190a3b5a081bbf46d55 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05c80a6088190a028967b682fed2b |
completed | March 22, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69c055f19b0c81908be34a00ab218723 |
completed | March 22, 2026, 8:49 p.m. |
Created at: March 22, 2026, 4:15 p.m.