Triple
T32895122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penny Fleck |
E841448
|
entity |
| Predicate | relationshipToArthurFleck |
P38921
|
FINISHED |
| Object | mother |
—
|
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: mother | Statement: [Penny Fleck, relationshipToArthurFleck, mother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToArthurFleck Context triple: [Penny Fleck, relationshipToArthurFleck, mother]
-
A.
relationshipToCharacter
chosen
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
B.
relationshipToClarkKent
Indicates the specific personal, social, or familial connection that one entity has to Clark Kent.
-
C.
relationshipToFalstaff
Indicates the specific interpersonal or social connection that one entity has to Falstaff.
-
D.
characterActorRelationship
Indicates a relationship where an actor portrays or is associated with a specific character in a work.
-
E.
hasFictionalRelationshipWith
Indicates that there exists a fictional or imagined relationship between two entities, such as characters in a story or hypothetical scenarios.
- 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_69f34945ae408190b72d8118c83beb77 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:18 a.m.