Triple
T4583734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fermina Daza |
E101915
|
entity |
| Predicate | socialMobility |
P58133
|
FINISHED |
| Object | rises in social status through marriage |
—
|
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: rises in social status through marriage | Statement: [Fermina Daza, socialMobility, rises in social status through marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: socialMobility Context triple: [Fermina Daza, socialMobility, rises in social status through marriage]
-
A.
socialComposition
Indicates the makeup or distribution of different social groups or categories within a population or community.
-
B.
socialPhenomenon
Indicates a relationship where an event, behavior, or pattern emerges from and affects interactions within a society or group.
-
C.
socialSphere
Indicates the social environment or network within which an entity regularly interacts or maintains relationships.
-
D.
socialCenter
Indicates that a place functions as a primary gathering point or hub for social interaction and community activities.
-
E.
visitorFrequency
Indicates how often a visitor comes to or interacts with a particular entity or location.
- 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_69bd43d4ce208190b53158c882b222e3 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd590411dc81909c55d1c42a4d44ef |
completed | March 20, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69bd522acbcc8190bf24d9517793a2c1 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56b4a9508190acdb888eef18f1ee |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:10 p.m.