Triple
T1259519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wizard of Menlo Park |
E12465
|
entity |
| Predicate | refersToField |
P6979
|
FINISHED |
| Object | electrical engineering |
—
|
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: electrical engineering | Statement: [The Wizard of Menlo Park, refersToField, electrical engineering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refersToField Context triple: [The Wizard of Menlo Park, refersToField, electrical engineering]
-
A.
relatedField
chosen
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
-
B.
refersToRole
Indicates that one entity designates, mentions, or points to another entity specifically in its capacity as a role or position.
-
C.
namedForField
Indicates that one entity is named after, or in honor of, a particular field, discipline, or area of study.
-
D.
refersToLocation
Indicates that one entity designates, points to, or identifies a specific location associated with it.
-
E.
isReferencePointFor
Indicates that one entity serves as a positional or conceptual basis used to locate, measure, or interpret another entity.
- 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfc3a2848190891e73b351019d5b |
completed | March 1, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6eefbc81908dddd7d2ef368186 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:50 p.m.