Triple
T25950274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Law & Order: Organized Crime |
E653949
|
entity |
| Predicate | franchisePeer |
P159850
|
FINISHED |
| Object | Law & Order |
—
|
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: Law & Order | Statement: [Law & Order: Organized Crime, franchisePeer, Law & Order]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: franchisePeer Context triple: [Law & Order: Organized Crime, franchisePeer, Law & Order]
-
A.
franchiseOf
Indicates that one entity operates as a franchise belonging to or licensed by another entity.
-
B.
franchiseConnection
Indicates a relationship where one entity is part of, derived from, or otherwise officially linked to a larger franchise or brand.
-
C.
franchiseElement
Indicates that one entity is a component, installment, or part within a larger franchise or series associated with another entity.
-
D.
franchiseBrand
Indicates that one entity is the brand under which another entity operates as a franchise.
-
E.
franchiseRelation
Indicates a relationship where one entity grants another the rights to operate under its brand, system, or business model as a franchise.
- F. None of above. chosen
Provenance (4 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_69e7ab40ac788190a771bc499eb1ae5f |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f60494d2808190b38f338685628eda |
completed | May 2, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69f5aff889988190ad10bcf1a280f717 |
completed | May 2, 2026, 8:04 a.m. |
| PDg | Predicate description generation | batch_69f5f6b32a8881909baa0db57b80d56a |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 22, 2026, 8:43 a.m.