Triple
T6600202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Longwood Gardens |
E148976
|
entity |
| Predicate | hasGreenhouseArea |
P47974
|
FINISHED |
| Object | over 4 acres under glass |
—
|
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: over 4 acres under glass | Statement: [Longwood Gardens, hasGreenhouseArea, over 4 acres under glass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGreenhouseArea Context triple: [Longwood Gardens, hasGreenhouseArea, over 4 acres under glass]
-
A.
hasGreenhouse
chosen
Indicates that an entity possesses or includes a greenhouse structure or facility.
-
B.
plantArea
Indicates the total surface area occupied or covered by a plant or group of plants.
-
C.
hasBotanicalGardenArea_ha
Indicates that an entity possesses a botanical garden whose area is measured in hectares.
-
D.
hasGreenSpaces
Indicates that an entity includes or is associated with areas of vegetation or natural greenery, such as parks, gardens, or lawns.
-
E.
hasIrrigationArea
Indicates that an entity possesses or is associated with a specific area of land equipped or designated for irrigation.
- 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_69c687eaa7508190bb58ce2aa02039b3 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cc9c6cb0819084fec8e0beb430de |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6acfd17388190bd0bb8b2371e7df1 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:56 p.m.