Triple
T6495271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fayga Ostrower |
E148141
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Fayga |
E558926
|
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: Fayga | Statement: [Fayga Ostrower, givenName, Fayga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fayga Context triple: [Fayga Ostrower, givenName, Fayga]
-
A.
Fayga
chosen
Fayga is a given name most notably borne by the Brazilian artist and printmaker Fayga Ostrower.
-
B.
Shughni
Shughni is an Eastern Iranian language spoken primarily in the Badakhshan region of Tajikistan and Afghanistan, known for its use among the Shughni people in the Pamir Mountains.
-
C.
Baiga
Baiga are an indigenous Adivasi community of central India known for their traditional shifting cultivation, forest-based livelihood, and distinctive cultural practices.
-
D.
Mishaninskaya
Mishaninskaya is a rural locality in Russia best known as the birthplace of the polymath and scientist Mikhail Lomonosov.
-
E.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
- 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_69c009088f3081909cd467b05919de30 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06ab958808190bd85e007e925ffc4 |
completed | March 22, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c653c21f948190989da451bc573b4d |
completed | March 27, 2026, 9:54 a.m. |
Created at: March 22, 2026, 4:53 p.m.