Triple
T20934562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ray Ozzie |
E515549
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ray Ozzie |
—
|
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: Ray Ozzie | Statement: [Ray Ozzie, name, Ray Ozzie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ray Ozzie Context triple: [Ray Ozzie, name, Ray Ozzie]
-
A.
Ray Ozzie
chosen
Ray Ozzie is an American software entrepreneur and technologist best known for creating Lotus Notes and later serving as a key strategic leader at Microsoft.
-
B.
Steve Case
Steve Case is an American entrepreneur and investor best known as the co-founder and former CEO of AOL, a pioneering internet services company.
-
C.
Mike Lynch
Mike Lynch is a collegiate athletics administrator best known for leading the athletic department at Babson College.
-
D.
Thomas Siebel
Thomas Siebel is an American technology entrepreneur best known as the founder of Siebel Systems and later the cloud computing company C3.ai.
-
E.
Urs Hölzle
Urs Hölzle is a Swiss computer scientist best known as one of Google’s first employees and its longtime Senior Vice President of Technical Infrastructure, where he has shaped the company’s large-scale computing systems.
- 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_69e0b4fc13408190b06868df03c5c29b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f94fc194819099df82357a7f33c7 |
completed | April 21, 2026, 4:13 a.m. |
Created at: April 16, 2026, 12:49 p.m.