Triple
T15405321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christmas Tree Lane |
E368436
|
entity |
| Predicate | treePlantingStartYear |
P71132
|
FINISHED |
| Object | 1880s |
—
|
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: 1880s | Statement: [Christmas Tree Lane, treePlantingStartYear, 1880s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treePlantingStartYear Context triple: [Christmas Tree Lane, treePlantingStartYear, 1880s]
-
A.
treePlanting
Indicates the action of placing and establishing a tree in the ground at a chosen location.
-
B.
plantedInYear
chosen
Indicates that something was planted or sown in a specific calendar year.
-
C.
treesPlantedBy
Indicates that one entity is responsible for planting or causing the planting of another entity (typically trees).
-
D.
plantedAt
Indicates that one entity has been planted or placed into the ground or a specific location at or in association with another entity.
-
E.
hasCherryTreesPlantedSince
Indicates that cherry trees have been planted on or at an entity starting from a specified point in time and continuing thereafter.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8fde64819082ec0c68df305561 |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27b8cac8190bfa77698d53c5d1c |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:20 a.m.