Triple
T4808490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doctor Thomas Thorne |
E107003
|
entity |
| Predicate | socialPosition |
P60246
|
FINISHED |
| Object | middle-class professional |
—
|
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: middle-class professional | Statement: [Doctor Thomas Thorne, socialPosition, middle-class professional]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: socialPosition Context triple: [Doctor Thomas Thorne, socialPosition, middle-class professional]
-
A.
socialStance
Indicates the attitude, position, or orientation one entity holds toward another in a social context.
-
B.
socialView
Indicates a relationship where one entity views, accesses, or inspects another entity’s social-related information, profile, or activity.
-
C.
socialType
Indicates the category or nature of a social relationship or interaction that exists between entities.
-
D.
socialComposition
Indicates the makeup or distribution of different social groups or categories within a population or community.
-
E.
socialSphere
Indicates the social environment or network within which an entity regularly interacts or maintains relationships.
- 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_69bd43f779448190b92885cb70abb6c2 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1c43a48190a65e56b1624a2339 |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6ff731188190a9903602122d4ff9 |
completed | March 20, 2026, 4:04 p.m. |
Created at: March 20, 2026, 1:23 p.m.