Triple
T9873080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sally Carrera |
E240004
|
entity |
| Predicate | locatedInFictionalUniverse |
P3758
|
FINISHED |
| Object | Cars universe |
E818182
|
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: Cars universe | Statement: [Sally Carrera, locatedInFictionalUniverse, Cars universe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cars universe Context triple: [Sally Carrera, locatedInFictionalUniverse, Cars universe]
-
A.
Cars universe
chosen
The Cars universe is the animated world created by Pixar in which anthropomorphic vehicles live, work, and race, as depicted in the Cars film series and related media.
-
B.
Carros
Carros is a commune in southeastern France situated in the Alpes-Maritimes department near Nice on the French Riviera.
-
C.
CAR
CAR is a research center dedicated to advancing the understanding, diagnosis, and treatment of autism spectrum disorders through scientific study and clinical collaboration.
-
D.
CAR
CAR is the standard three-letter abbreviation used for the NFL team Carolina Panthers.
-
E.
CAR
CAR is the National Rail station code for Carlisle railway station in Cumbria, England.
- 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_69ca84e8a0788190b9061811d50fd554 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3f754008190abe3fe034b42908e |
completed | April 2, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e46f18148190a36af7e7d7487205 |
completed | April 5, 2026, 4:26 a.m. |
Created at: March 30, 2026, 8:37 p.m.