Triple
T29243361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leersia |
E741367
|
entity |
| Predicate | reasonForCommonName |
P7885
|
FINISHED |
| Object | sharp leaf blades that can cut skin |
—
|
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: sharp leaf blades that can cut skin | Statement: [Leersia, reasonForCommonName, sharp leaf blades that can cut skin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForCommonName Context triple: [Leersia, reasonForCommonName, sharp leaf blades that can cut skin]
-
A.
reasonForName
chosen
Indicates the explanation or cause behind why an entity has a particular name.
-
B.
commonName
Indicates that one entity is the commonly used or vernacular name by which the other entity is known.
-
C.
commonNameOf
Indicates that one entity is the commonly used or popular name by which the other entity is known.
-
D.
otherCommonName
Indicates that an entity is known by an additional, alternative common name besides its primary one.
-
E.
alsoKnownAsReason
Indicates that an alternative name or alias is used for an entity specifically because of the stated reason.
- 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_69f0911dd6fc819097d1abb287016489 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f79f48acec8190a9d5964581a94f6c |
completed | May 3, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
Created at: April 28, 2026, 12:31 p.m.