Triple
T27618973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | O Tannenbaum |
E700516
|
entity |
| Predicate | hasEnglishFirstLine |
P67696
|
FINISHED |
| Object | O Christmas Tree, O Christmas Tree, how lovely are thy branches |
—
|
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: O Christmas Tree, O Christmas Tree, how lovely are thy branches | Statement: [O Tannenbaum, hasEnglishFirstLine, O Christmas Tree, O Christmas Tree, how lovely are thy branches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnglishFirstLine Context triple: [O Tannenbaum, hasEnglishFirstLine, O Christmas Tree, O Christmas Tree, how lovely are thy branches]
-
A.
hasEnglishIncipit
chosen
Indicates that an entity has an opening phrase or initial text (incipit) expressed in English.
-
B.
hasEnglishEdition
Indicates that one entity has a version or edition of itself that is produced or available in the English language.
-
C.
hasTitleInEnglishOrthography
Indicates that an entity has a specific title expressed using English spelling and writing conventions.
-
D.
hasPrimaryLanguage1
Indicates that an entity’s main or most commonly used language is the specified language.
-
E.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
- F. None of above.
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_69ef6a4f1d9c8190b0705acda054368d |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 27, 2026, 2:13 p.m.