Triple
T26579169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oliver |
E667028
|
entity |
| Predicate | appearsInCrossover |
P158201
|
FINISHED |
| Object | Lab Rats |
—
|
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: Lab Rats | Statement: [Oliver, appearsInCrossover, Lab Rats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsInCrossover Context triple: [Oliver, appearsInCrossover, Lab Rats]
-
A.
appearsIn
Indicates that an entity is present, featured, or occurs within a particular context, work, or medium.
-
B.
franchiseCrossover
chosen
Indicates a relationship where characters, elements, or storylines from one fictional franchise appear within or interact with those of another franchise.
-
C.
appearsInContinuity
Indicates that an entity is part of, or occurs within, a specific narrative continuity or canon timeline.
-
D.
appearsAgainst
Indicates that one entity is visually or publicly presented in opposition to, or in contrast with, another entity.
-
E.
appearedInEpisodeOf
Indicates that one entity made an appearance in a specific episode belonging to a television or radio series associated with the other 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_69ee9cfb7e548190b60a9031182f5a7e |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f67c9fe7b48190b79b4041357edb49 |
completed | May 2, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69f678cc272081909e5c70f1bc7407f0 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 27, 2026, 2:02 a.m.