Triple
T364454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jobs |
E7927
|
entity |
| Predicate | associatedFieldThroughBearers |
P2531
|
FINISHED |
| Object | technology industry |
—
|
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: technology industry | Statement: [Jobs, associatedFieldThroughBearers, technology industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedFieldThroughBearers Context triple: [Jobs, associatedFieldThroughBearers, technology industry]
-
A.
hasNotableFieldOfBearers
chosen
Indicates that the entities share a significant or distinguished area of activity, expertise, or achievement associated with their bearers.
-
B.
relatedField
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
-
C.
associatedState
Indicates that one entity is linked or connected to a particular state, condition, or status of another entity.
-
D.
isAssociatedWith
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
E.
associatedWithText
Indicates that an entity has a contextual or semantic connection to a specific piece of text.
- 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_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. |
Created at: Feb. 28, 2026, 1:08 p.m.