Triple
T1536402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Lady of California |
E32558
|
entity |
| Predicate | mayFocusOn |
P7233
|
FINISHED |
| Object | education-related causes |
—
|
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: education-related causes | Statement: [Second Lady of California, mayFocusOn, education-related causes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayFocusOn Context triple: [Second Lady of California, mayFocusOn, education-related causes]
-
A.
mayProvideFocus
chosen
Indicates that one entity can potentially direct attention, emphasis, or concentration toward another entity or aspect.
-
B.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
C.
mayHold
Indicates that one entity is permitted or allowed to possess, contain, or maintain another entity.
-
D.
mayAdvanceTo
Indicates that one entity is permitted or eligible to progress, move, or be promoted to another specified state, level, or position.
-
E.
mayExtendTo
Indicates that something has the potential or permission to reach, continue, or be applied up to a specified limit, scope, or boundary.
- 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.