Triple
T12793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California redwood |
E257
|
entity |
| Predicate | distribution |
P1356
|
FINISHED |
| Object | northern California coast |
—
|
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: northern California coast | Statement: [California redwood, distribution, northern California coast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distribution Context triple: [California redwood, distribution, northern California coast]
-
A.
sector
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
-
B.
dissolved
Indicates that one substance has been mixed into another so thoroughly that it forms a uniform solution and is no longer distinguishable as a separate phase.
-
C.
category
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
D.
requires
Indicates that one entity must exist, occur, or be satisfied before another entity can exist, occur, or be carried out.
-
E.
demographics
Indicates the relationship of providing or characterizing statistical information about a population’s attributes, such as age, gender, income, or education.
- F. None of above. chosen
Provenance (4 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a243abb2ec8190937365e5ecec52ad |
completed | Feb. 28, 2026, 1:23 a.m. |
| PD | Predicate disambiguation | batch_69a23fe9470c8190918a6ca1df168646 |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a243aa85848190813154e8a6495200 |
completed | Feb. 28, 2026, 1:23 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.