Triple
T379565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Grow the Lilacs |
E8647
|
entity |
| Predicate | titleDerivedFrom |
P12689
|
FINISHED |
| Object | traditional folk song "Green Grow the Lilacs" |
—
|
LITERAL 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: traditional folk song "Green Grow the Lilacs" | Statement: [Green Grow the Lilacs, titleDerivedFrom, traditional folk song "Green Grow the Lilacs"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleDerivedFrom Context triple: [Green Grow the Lilacs, titleDerivedFrom, traditional folk song "Green Grow the Lilacs"]
-
A.
title
Indicates that one entity serves as the formal name or designation of another entity.
-
B.
titleType
Indicates the specific category or kind of title associated with an entity (e.g., whether it is a main title, alternative title, working title, etc.).
-
C.
titleMeaning
Indicates that one entity expresses or explains the meaning, significance, or interpretation of another entity’s title.
-
D.
titleInEnglish
Indicates that an entity’s title or name is given in the English language.
-
E.
associatedTitle
Indicates that one entity has a title, designation, or formal label that is linked or relevant to another entity.
- F. None of above. chosen
Provenance (4 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec2b07248190979229bad3a741c9 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e964d4b481909290e474b0341e3c |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2eae0bd7081908197bbf5c55fe647 |
completed | Feb. 28, 2026, 1:17 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.