Triple
T15165795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Grubbs |
E362337
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Grubbs |
E773025
|
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: Grubbs | Statement: [David Grubbs, familyName, Grubbs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grubbs Context triple: [David Grubbs, familyName, Grubbs]
-
A.
Grubbs
chosen
Grubbs is a surname most prominently associated with Nobel Prize–winning chemist Robert H. Grubbs, known for his pioneering work in olefin metathesis.
-
B.
Grubbs' test
Grubbs' test is a statistical hypothesis test used to detect a single outlier in a univariate data set that is approximately normally distributed.
-
C.
Tukey
Tukey is the surname of John W. Tukey, a prominent American statistician known for pioneering exploratory data analysis and coining the term "bit."
-
D.
Geiringer
Geiringer is a surname most notably associated with Hilda Geiringer, an Austrian-American mathematician known for her contributions to applied mathematics and probability theory.
-
E.
Hartigan
Hartigan is a surname most notably associated with Grace Hartigan, a prominent American Abstract Expressionist painter.
- 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_69d85a087b7c81908baa94a53dac8d68 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0064c6244819085daf8e1eafdf3f2 |
completed | April 15, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec887fbf08190b42dd25a99b7770d |
completed | May 9, 2026, 5:39 a.m. |
Created at: April 10, 2026, 3:08 a.m.