Triple
T276170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claude Monet |
E5253
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Claude |
E1167
|
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: Claude | Statement: [Claude Monet, givenName, Claude]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Claude Context triple: [Claude Monet, givenName, Claude]
-
A.
Claude
chosen
Claude is a given name most famously associated with Claude Shannon, the American mathematician and electrical engineer known as the father of information theory.
-
B.
Michel
Michel is the birth name of the acclaimed Egyptian actor Omar Sharif, renowned for his roles in classic films such as "Lawrence of Arabia" and "Doctor Zhivago."
-
C.
DALL·E
DALL·E is an AI model developed by OpenAI that generates images from natural language descriptions, enabling text-to-image synthesis.
-
D.
André
André is a given name of French origin commonly used in various languages as a form of "Andrew."
-
E.
Jacques
Jacques is the French form of the given name James, commonly used in French-speaking countries.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25dec53ac8190912f3d79576131fa |
completed | Feb. 28, 2026, 3:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a391525a7081909166884a8ea47ace |
completed | March 1, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.