Triple
T21746883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rob Crow |
E536811
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Rob |
—
|
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: Rob | Statement: [Rob Crow, hasGivenName, Rob]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rob Context triple: [Rob Crow, hasGivenName, Rob]
-
A.
Rob
chosen
Rob is a common shortened form of the given name Robert, frequently used as an informal or familiar first name.
-
B.
Ron
Ron is a male given name commonly used in English-speaking countries, often as a short form of Ronald.
-
C.
Ron
Ron is the commonly used first name of American politician Ron DeSantis, the governor of Florida and a prominent figure in contemporary U.S. conservative politics.
-
D.
Ron
Ron is a West Chadic language spoken in parts of central Nigeria.
-
E.
Ron
Ron is a malfunctioning but endearing robot companion who forms an unlikely friendship with a socially awkward boy in the animated film "Ron's Gone Wrong."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c46df5448190b4322127ffc4c690 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01a771b908190886cade242e263e4 |
completed | April 28, 2026, 2:24 a.m. |
Created at: April 16, 2026, 6:49 p.m.