Triple
T31451270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Lady of Texas |
E802325
|
entity |
| Predicate | isCustomarilyAddressedAs |
P148938
|
FINISHED |
| Object | First Lady [surname] |
—
|
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: First Lady [surname] | Statement: [First Lady of Texas, isCustomarilyAddressedAs, First Lady [surname]]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCustomarilyAddressedAs Context triple: [First Lady of Texas, isCustomarilyAddressedAs, First Lady [surname]]
-
A.
hasAffectionateNicknameFor
Indicates that one entity uses or assigns a fond, affectionate, or endearing nickname to another entity.
-
B.
addressingType
Indicates the manner or form in which one entity addresses or refers to another (e.g., formally, informally, by title, or by name).
-
C.
wasAddressedAs
chosen
Indicates that one entity referred to or called another entity by a particular name, title, or form of address.
-
D.
honorificNickname
Indicates that one entity is referred to by a respectful or honorific nickname by another entity or in a given context.
-
E.
givenNameFor
Indicates that one entity is the personal first name assigned to or used for another entity.
- 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_69f348c678ac81908a2e950867619061 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a5f71b2c8190aade8a83f465be0c |
completed | May 3, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69f69fe66df08190958558d63ee623d9 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 30, 2026, 9:13 p.m.