Triple
T29363536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chloe Carmichael |
E744654
|
entity |
| Predicate | sharesEpisodeFocusWith |
P123175
|
FINISHED |
| Object | Timmy Turner |
—
|
NE NERFINISHED |
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: Timmy Turner | Statement: [Chloe Carmichael, sharesEpisodeFocusWith, Timmy Turner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesEpisodeFocusWith Context triple: [Chloe Carmichael, sharesEpisodeFocusWith, Timmy Turner]
-
A.
sharesEpisodeWith
chosen
Indicates that two entities appear in or are associated with the same episode of a series or program.
-
B.
sharesUniverseWith
Indicates that two entities exist within the same fictional or narrative universe, implying shared continuity, setting, or canon.
-
C.
sharesInteractionPointWith
Indicates that two entities have at least one common point or location at which they can interact or make contact with each other.
-
D.
sharesFeatureWith
Indicates that two entities have at least one common attribute, property, or characteristic in common.
-
E.
sharesSubjectWith
Indicates that two items are associated with or pertain to the same subject or topic.
- 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_69f0a79aee588190b490f19d93c6e52d |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fddac4e2f48190a9301d3422658b29 |
completed | May 8, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69fdda06969c8190b5d033964ea2a690 |
completed | May 8, 2026, 12:41 p.m. |
Created at: April 28, 2026, 2:20 p.m.