Triple
T7713830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gawker Media |
E174831
|
entity |
| Predicate | parentCompanyOf |
P254
|
FINISHED |
| Object | Jalopnik |
E682566
|
NE 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: Jalopnik | Statement: [Gawker Media, parentCompanyOf, Jalopnik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jalopnik Context triple: [Gawker Media, parentCompanyOf, Jalopnik]
-
A.
Jalopnik
chosen
Jalopnik is an automotive-focused news and culture website known for its car reviews, industry commentary, and enthusiast-oriented coverage.
-
B.
Hot Rod
Hot Rod is a 2007 comedy film starring Andy Samberg as an inept stuntman attempting a massive jump to earn money for his stepfather’s surgery.
-
C.
Carros
Carros is a commune in southeastern France situated in the Alpes-Maritimes department near Nice on the French Riviera.
-
D.
Motor Mania
Motor Mania is a 1950 Disney animated short film featuring Goofy that humorously depicts the transformation of a mild-mannered driver into an aggressive road menace.
-
E.
L’Auto
L’Auto was a French sports newspaper best known for creating and organizing the Tour de France.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6995c463c8190a14458036249d419 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702ca8f048190a6ea27b8cee2f93e |
completed | March 27, 2026, 10:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8b508fa2081908ed05ca8c4815249 |
completed | March 29, 2026, 5:13 a.m. |
Created at: March 27, 2026, 4:04 p.m.