Triple
T1536385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Lady of California |
E32558
|
entity |
| Predicate | feminineFormOf |
P17779
|
FINISHED |
| Object | Second Spouse of California |
—
|
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: Second Spouse of California | Statement: [Second Lady of California, feminineFormOf, Second Spouse of California]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: feminineFormOf Context triple: [Second Lady of California, feminineFormOf, Second Spouse of California]
-
A.
genderedFormOf
chosen
Indicates that one term is a gender-specific variant or inflected form corresponding to another, more neutral or differently gendered term.
-
B.
genderNeutralForm
Indicates that one entity is a gender-neutral linguistic form or expression corresponding to another, more gendered form.
-
C.
nounFormOf
Indicates that one term is the noun form derived from, or corresponding to, another term (typically a verb or adjective).
-
D.
hasMasculineForm
Indicates that an entity has a corresponding masculine grammatical or lexical form.
-
E.
isGivenNameFormOf
Indicates that one name is a given-name variant or form derived from another name.
- 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_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. |
Created at: March 4, 2026, 7:26 p.m.