Triple
T12491798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Insitro |
E298582
|
entity |
| Predicate | hasKeyPerson |
P256
|
FINISHED |
| Object | Daphne Koller |
E61924
|
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: Daphne Koller | Statement: [Insitro, hasKeyPerson, Daphne Koller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daphne Koller Context triple: [Insitro, hasKeyPerson, Daphne Koller]
-
A.
Daphne Koller
chosen
Daphne Koller is a computer scientist and entrepreneur best known as the co-founder of the online education platform Coursera and for her influential work in probabilistic graphical models and machine learning.
-
B.
Andrew B. Moore
Andrew B. Moore was an American politician who served as governor of Alabama in the years leading up to and during the early part of the Civil War.
-
C.
Jure Leskovec
Jure Leskovec is a prominent computer scientist known for his influential work in data mining, social network analysis, and machine learning, particularly on large-scale graph data.
-
D.
Michael P. Kearns
Michael P. Kearns is an American politician from New York who has served in various local and state offices, including roles in the New York State Assembly and Erie County government.
-
E.
Jon Kleinberg
Jon Kleinberg is a prominent computer scientist known for his influential work in algorithms, networks, and data science, particularly in the analysis of large-scale social and information networks.
- 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_69d6ada377208190a36011199a4d8558 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94de3076c81909640c982d520ca6b |
completed | April 10, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6556e9180819084ddb984754b0b54 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 9:56 p.m.