Triple
T5931586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuber melanosporum |
E131949
|
entity |
| Predicate | formsMycorrhizaWith |
P66798
|
FINISHED |
| Object | oak trees |
—
|
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: oak trees | Statement: [Tuber melanosporum, formsMycorrhizaWith, oak trees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formsMycorrhizaWith Context triple: [Tuber melanosporum, formsMycorrhizaWith, oak trees]
-
A.
formsWith
Indicates that one entity combines or associates with another to create or constitute a joint structure, group, or configuration.
-
B.
rhizoidType
Indicates the specific kind or category of rhizoid structure associated with an organism or anatomical feature.
-
C.
hasRhizoids
Indicates that an organism possesses rhizoids, i.e., root-like structures used for anchorage or absorption.
-
D.
formsIn
Indicates that one entity takes shape, develops, or comes into existence within or inside another entity.
-
E.
associatedFormation
Indicates that one entity is linked or connected to a particular formation, such as a geological, structural, or organizational configuration.
- 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c033541d108190a34d1fde2fe9dacb |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c03c8d579081909d7b97fc9014b5d7 |
completed | March 22, 2026, 7:01 p.m. |
Created at: March 22, 2026, 4 p.m.