Triple
T1328543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trema |
E28386
|
entity |
| Predicate | colonizes |
P27264
|
FINISHED |
| Object | roadsides |
—
|
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: roadsides | Statement: [Trema, colonizes, roadsides]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colonizes Context triple: [Trema, colonizes, roadsides]
-
A.
colonized
Indicates that one entity established control over and settled in the territory of another entity, often imposing its own systems, structures, or population there.
-
B.
colonyOf
Indicates that one entity is a colony belonging to, founded by, or politically dependent on another entity.
-
C.
parasitizes
Indicates a relationship in which one organism lives on or in another organism, deriving nutrients or benefits at the host’s expense.
-
D.
occupies
Indicates that one entity takes up or resides within a physical or conceptual space belonging to or associated with another entity.
-
E.
colonialOffshoot
Indicates that one entity originated as a colony or derivative settlement established by another entity.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1c1d8188190b15a641a08345adc |
completed | March 1, 2026, 10:46 p.m. |
| PD | Predicate disambiguation | batch_69a4beef6a188190996f8775bdda8f6c |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c0b1326081909aa6beec0cfe8d6c |
completed | March 1, 2026, 10:41 p.m. |
Created at: March 1, 2026, 7:55 p.m.