Triple
T188826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pierre |
E3672
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Pierrot |
E3672
|
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: Pierrot | Statement: [Pierre, hasVariant, Pierrot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pierrot Context triple: [Pierre, hasVariant, Pierrot]
-
A.
Pierre
chosen
Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
-
B.
Jacques
Jacques is the French form of the given name James, commonly used in French-speaking countries.
-
C.
Madam
"Madam" is a formal term of address for a woman, often used to show respect or politeness in social, professional, or official contexts.
-
D.
Don Juan
Don Juan is a long satirical narrative poem by Lord Byron that humorously reimagines the legendary libertine as a naïve young man swept through a series of romantic and political adventures.
-
E.
Georges
Georges is a masculine given name of Greek origin, commonly used in French-speaking countries and derived from the name George, meaning "farmer" or "earthworker."
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a2594abeec8190a48f36817e647fcd |
completed | Feb. 28, 2026, 2:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a30287094c8190ad4669e856a29f6c |
completed | Feb. 28, 2026, 2:58 p.m. |
Created at: Feb. 28, 2026, 2:41 a.m.