Triple
T1532558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simon van der Meer |
E32476
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Simon |
E48166
|
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: Simon | Statement: [Simon van der Meer, givenName, Simon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Simon Context triple: [Simon van der Meer, givenName, Simon]
-
A.
Simon
chosen
Simon is the given name of Simon Bolivar Buckner Jr., a U.S. Army lieutenant general who was killed in action while commanding forces during the Battle of Okinawa in World War II.
-
B.
Sam
Sam is a person whose given name is Sam.
-
C.
Sid
Sid is a minor character in Mark Twain's novel "The Adventures of Tom Sawyer," known as Tom's well-behaved, tattletale half-brother who often contrasts Tom's mischievous nature.
-
D.
Jack
Jack is a common masculine given name, often used as a familiar form of John and widely featured in English-language literature and popular culture.
-
E.
Charlie
Charlie is the fictional Boston subway rider in the folk song "Charlie on the MTA," known for being unable to get off the train because he lacks the fare to exit.
- 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_69a885ea86308190998f6bc14bb91f8e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9081835e4819093dee004fdb027ff |
completed | March 5, 2026, 4:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad295a03d881909071fb437c2d19ba |
completed | March 8, 2026, 7:46 a.m. |
Created at: March 4, 2026, 7:26 p.m.