Triple
T18252483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard R. Schrock |
E437128
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Schrock |
—
|
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: Schrock | Statement: [Richard R. Schrock, familyName, Schrock]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schrock Context triple: [Richard R. Schrock, familyName, Schrock]
-
A.
Schrock
chosen
Schrock is the surname of Richard R. Schrock, an American chemist and Nobel laureate known for his work on olefin metathesis.
-
B.
Schucht
Schucht is an Italian surname most notably associated with Giulia Schucht, the wife of Russian revolutionary Vladimir Lenin.
-
C.
Shook
Shook is a surname most notably associated with Karel Shook, an influential American ballet dancer, teacher, and co-founder of the Dance Theatre of Harlem.
-
D.
Fearing
Fearing is a given name most notably associated with Rufus Fearing Dawes, an American Civil War officer and politician.
-
E.
Scarness
Scarness is a coastal suburb and beachside community within Hervey Bay in Queensland, Australia, known for its foreshore parks, jetty, and tourist amenities.
- 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_69d8b91104e08190a8241f7d260a5162 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4fd81ea3481909d96b5399f7a32b3 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 10:33 a.m.