Triple
T364453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jobs |
E7927
|
entity |
| Predicate | semanticRelation |
P12753
|
FINISHED |
| Object | homographOf "jobs" (plural of job) |
—
|
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: homographOf "jobs" (plural of job) | Statement: [Jobs, semanticRelation, homographOf "jobs" (plural of job)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: semanticRelation Context triple: [Jobs, semanticRelation, homographOf "jobs" (plural of job)]
-
A.
semanticType
Indicates that something belongs to or is categorized under a particular semantic class or type based on its meaning.
-
B.
temporalRelation
Indicates a relationship that specifies how two events or states are positioned relative to each other in time (e.g., before, after, or overlapping).
-
C.
definesRelationshipBetween
Indicates that one entity specifies or establishes the nature, type, or rules of a relationship that exists between two or more other entities.
-
D.
relatedField
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
-
E.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebe6c1b4819083335e880c205ed6 |
completed | Feb. 28, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69a2e95dbb208190b277fc5352a4ee84 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2eafc8da88190b4a05182f4384442 |
completed | Feb. 28, 2026, 1:17 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.