Triple
T11351498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lightning |
E268848
|
entity |
| Predicate | portGender |
P51173
|
FINISHED |
| Object | female receptacle |
—
|
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: female receptacle | Statement: [Lightning, portGender, female receptacle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portGender Context triple: [Lightning, portGender, female receptacle]
-
A.
plugGender
chosen
Indicates that one entity’s connector has a specified gender (e.g., male, female, neutral) in relation to another connector or interface.
-
B.
hasGenderInPortuguese
Indicates that a term or entity is associated with a specific grammatical gender in the Portuguese language.
-
C.
hasGenderInterpretation
Indicates that an entity is associated with a particular interpretation or understanding of gender.
-
D.
playsGender
Indicates that one entity performs or assumes a particular gender role or identity in a given context.
-
E.
portLocation
Indicates that a port is geographically situated at or associated with a specific location.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d80148e2048190a716b515d78efdd1 |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e6f8aeb4819080476f16a69b2ee3 |
completed | April 9, 2026, 5:50 p.m. |
Created at: April 8, 2026, 9:33 p.m.