Triple
T12367134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlantic white cedar forest |
E294901
|
entity |
| Predicate | typicallyOccursIn |
P91034
|
FINISHED |
| Object | coastal plain |
—
|
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: coastal plain | Statement: [Atlantic white cedar forest, typicallyOccursIn, coastal plain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicallyOccursIn Context triple: [Atlantic white cedar forest, typicallyOccursIn, coastal plain]
-
A.
sometimesLocatedIn
Indicates that an entity is located in a given place only at certain times or under certain conditions, rather than permanently or always.
-
B.
occurredIn
Indicates that an event or action took place within a specific location, context, or time frame.
-
C.
takesPlaceInRegion
Indicates that an event or occurrence happens within the boundaries of a specified geographic or administrative region.
-
D.
typicallyHeldIn
Indicates that an event, activity, or process most commonly or usually takes place within a particular location, venue, or context.
-
E.
oftenLocatedAt
chosen
Indicates that an entity is frequently or commonly found at, or associated with being in, a particular location.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d942a2d6e08190a13c7ff89af09354 |
completed | April 10, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69d93ecf6b548190a394b6b56a0c1c68 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.