Triple
T6745293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parker Harris |
E154194
|
entity |
| Predicate | hasLeadershipArea |
P49097
|
FINISHED |
| Object | technology strategy at Salesforce |
—
|
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 strategy at Salesforce | Statement: [Parker Harris, hasLeadershipArea, technology strategy at Salesforce]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLeadershipArea Context triple: [Parker Harris, hasLeadershipArea, technology strategy at Salesforce]
-
A.
hasLieutenancyArea
Indicates that an entity falls within, is administered by, or is associated with a specific lieutenancy area (a ceremonial or administrative jurisdiction).
-
B.
areaOfAuthority
chosen
Indicates the domain, region, or scope within which an entity has official power, control, or responsibility.
-
C.
governanceArea
Indicates the geographic or jurisdictional area over which an entity has governing authority or responsibility.
-
D.
hasLandmarkArea
Indicates that a specified area is designated as the landmark area associated with a particular entity or location.
-
E.
hasCivilArea
Indicates that an administrative or political entity encompasses or is associated with a specific civil (local administrative) area.
- 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_69c6880ef37881909268a5a7299b9293 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1b74ae081908575c4e47c0ef297 |
completed | March 27, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69c6d09067a0819087ed6c820f4699f8 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:10 p.m.