Triple
T1536408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Lady of California |
E32558
|
entity |
| Predicate | honorificNature |
P29607
|
FINISHED |
| Object | largely ceremonial |
—
|
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: largely ceremonial | Statement: [Second Lady of California, honorificNature, largely ceremonial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honorificNature Context triple: [Second Lady of California, honorificNature, largely ceremonial]
-
A.
honorificSense
Indicates that one entity refers to another using an honorific or respectful linguistic form.
-
B.
honorificType
Indicates the type or category of honorific or formal title associated with an entity in a given context.
-
C.
honorificDescription
Indicates that one entity is described using an honorific or respectful title or phrase referring to another entity.
-
D.
honorificNickname
Indicates that one entity is referred to by a respectful or honorific nickname by another entity or in a given context.
-
E.
honorificSuffix
Indicates that one entity is a respectful or formal suffix appended to another entity’s name or title.
- 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_69a885ea86308190998f6bc14bb91f8e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a915f323bc8190aa757142c225e0ae |
completed | March 5, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69a907b046448190be8ea4d7b20255f7 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a915f1694081908f87b509eda1309f |
completed | March 5, 2026, 5:34 a.m. |
Created at: March 4, 2026, 7:26 p.m.