Triple
T458248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mayor of Toronto |
E7277
|
entity |
| Predicate | hasHadOfficeHolder |
P9949
|
FINISHED |
| Object | Nathan Phillips |
E89128
|
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: Nathan Phillips | Statement: [Mayor of Toronto, hasHadOfficeHolder, Nathan Phillips]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nathan Phillips Context triple: [Mayor of Toronto, hasHadOfficeHolder, Nathan Phillips]
-
A.
Nathan Phillips
chosen
Nathan Phillips was a prominent Canadian politician who served as the reform-minded mayor of Toronto in the 1950s and early 1960s.
-
B.
Eric Thibault
Eric Thibault is a professional basketball coach best known for leading the WNBA’s Washington Mystics.
-
C.
Russell Dupuis
Russell Dupuis is an American electrical engineer and materials scientist renowned for his pioneering work in metal-organic chemical vapor deposition (MOCVD) and the development of semiconductor lasers and LEDs.
-
D.
Matt Johnston
Matt Johnston is a software developer best known as the creator and maintainer of the lightweight Dropbear SSH server and client suite.
-
E.
Tim Gardner
Tim Gardner is a neuroscientist and entrepreneur known for co-founding Neuralink, a company developing advanced brain–computer interface technology.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2f01ec5148190b74e1727712f1163 |
completed | Feb. 28, 2026, 1:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a65e2e20c08190af76454812a0c88b |
completed | March 3, 2026, 4:06 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.