Triple
T15752655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clara Stahlbaum |
E381883
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Masha |
E370387
|
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: Masha | Statement: [Clara Stahlbaum, alsoKnownAs, Masha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Masha Context triple: [Clara Stahlbaum, alsoKnownAs, Masha]
-
A.
Masha
chosen
Masha is a diminutive and affectionate Russian form of the given name Mary (Maria).
-
B.
Masha
Masha is a town in southwestern Ethiopia that serves as an administrative and commercial center in the Sheka Zone.
-
C.
Marichka
Marichka is a key supporting character in the dystopian film "Children of Men," known for helping protect the first pregnant woman in years.
-
D.
Mishka
Mishka is a reggae-influenced singer-songwriter known for his mellow, island-inspired sound and collaborations within the jam and surf music scenes.
-
E.
Mashenka
Mashenka is a Russian diminutive form of the female given name Maria, often used affectionately for girls and women.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e05030e31081908c307a8dc7067db4 |
completed | April 16, 2026, 2:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff876f005c8190913dec49b839b9f9 |
completed | May 9, 2026, 7:13 p.m. |
Created at: April 10, 2026, 4:47 a.m.