Triple
T17441101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oak Alley Plantation |
E424652
|
entity |
| Predicate | numberOfLiveOaksInAlley |
P25753
|
FINISHED |
| Object | 28 |
—
|
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: 28 | Statement: [Oak Alley Plantation, numberOfLiveOaksInAlley, 28]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfLiveOaksInAlley Context triple: [Oak Alley Plantation, numberOfLiveOaksInAlley, 28]
-
A.
avenueOfOaksPlantedBetween
Indicates that a line or avenue of oak trees has been planted between two specified locations or features.
-
B.
numberOfTrees
chosen
Indicates the count or quantity of trees associated with a given entity or context.
-
C.
hasAlley
Indicates that one entity possesses, includes, or is connected to an alley as part of its structure, layout, or surroundings.
-
D.
hasTreeLinedStreets
Indicates that the streets in a given area are lined or bordered with trees along their sides.
-
E.
numberOfPlants
Indicates the total count of plants associated with a given entity or context.
- 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44ff75538819083f77756d39a1aaa |
completed | April 19, 2026, 3:45 a.m. |
| PD | Predicate disambiguation | batch_69e3b030eac481909b8402719cc3102e |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:46 a.m.