Triple
T17257927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mikhail Vrubel |
E418930
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Lilac |
E968025
|
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: Lilac | Statement: [Mikhail Vrubel, notableWork, Lilac]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lilac Context triple: [Mikhail Vrubel, notableWork, Lilac]
-
A.
Syringa
chosen
Syringa is a genus of flowering woody plants commonly known as lilacs, prized for their fragrant, showy spring blossoms and widespread use as ornamental garden shrubs.
-
B.
Lilacs
"Lilacs" is a short story by Kate Chopin, included in her 1897 collection *A Night in Acadie*, that reflects her characteristic focus on intimate emotional experiences and Creole life.
-
C.
Lilacs
"Lilacs" is a notable work by American composer George Walker, recognized for its poignant musical setting of Walt Whitman’s elegy on the death of Abraham Lincoln.
-
D.
Lavender
"Lavender" is a song by Swedish rapper Yung Lean, known for its melancholic, atmospheric style and association with the early cloud rap and Sad Boys aesthetic.
-
E.
Lavender
Lavender is a feminine given name, often associated with the fragrant purple flower and used in English-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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e6dde4881908e7fc01fd5364616 |
completed | April 19, 2026, 1:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0170ff6818819090077dc4a7b774ae |
completed | May 11, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:39 a.m.