Triple
T4138433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lasius niger |
E89212
|
entity |
| Predicate | nuptialFlightTrigger |
P54096
|
FINISHED |
| Object | warm humid weather |
—
|
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: warm humid weather | Statement: [Lasius niger, nuptialFlightTrigger, warm humid weather]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nuptialFlightTrigger Context triple: [Lasius niger, nuptialFlightTrigger, warm humid weather]
-
A.
bride
Indicates that an entity is a woman who is getting married or has just been married in relation to a wedding event or spouse.
-
B.
engagedTo
Indicates that two entities are formally committed to marry each other.
-
C.
premiereOccasion
Indicates the event or context in which something (such as a work, show, or product) is first publicly presented or launched.
-
D.
hasPublicCeremony
Indicates that a public ceremony is held or conducted in relation to the subject entity.
-
E.
marries
Indicates that one entity enters into a legally or socially recognized marital union with 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_69aed95785788190ae75bcf0cd1cafdf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af018a54848190987f18c066c75068 |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af039fb19c8190b20e62a3b3ad25c1 |
completed | March 9, 2026, 5:30 p.m. |
Created at: March 9, 2026, 3:43 p.m.