Triple
T484825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linus |
E9851
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Linus van Pelt |
E9851
|
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: Linus van Pelt | Statement: [Linus, hasNotableBearer, Linus van Pelt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linus van Pelt Context triple: [Linus, hasNotableBearer, Linus van Pelt]
-
A.
Linus
chosen
Linus is a given name most famously associated with Linus Pauling, the American chemist and two-time Nobel Prize laureate.
-
B.
Ralph
Ralph is the given name of Ralph Waldo Emerson, the influential 19th-century American essayist, lecturer, philosopher, and central figure of the Transcendentalist movement.
-
C.
Bert
Bert is the given name of Bert Hölldobler, a renowned German behavioral biologist and sociobiologist known for his pioneering research on ants and social insects.
-
D.
Willy
Willy is a common diminutive form of the given name William, often used as an informal or affectionate nickname.
-
E.
Rudolph
Rudolph is the legendary red-nosed reindeer from Christmas folklore who guides Santa Claus’s sleigh through the night.
- 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_69a2e802e2908190ab17c9479e0b6412 |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f0bb46788190b40182bf2a54f98f |
completed | Feb. 28, 2026, 1:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a471205b9081908e75db702e9b3530 |
completed | March 1, 2026, 5:02 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.