Triple
T35925001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Lady of Illinois |
E1038994
|
entity |
| Predicate | hasAlternativeFormOfTitle |
P110696
|
FINISHED |
| Object | First Lady of the State of Illinois |
—
|
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 of the State of Illinois | Statement: [First Lady of Illinois, hasAlternativeFormOfTitle, First Lady of the State of Illinois]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternativeFormOfTitle Context triple: [First Lady of Illinois, hasAlternativeFormOfTitle, First Lady of the State of Illinois]
-
A.
haveAlternativeTitle
chosen
Indicates that an entity is known by one or more alternative titles or names in addition to its primary title.
-
B.
hasAlternativeTitleStyle
Indicates that an entity is associated with an alternative stylistic form or variation of its title.
-
C.
hasAlternativeTitleCombination
Indicates that an entity is associated with one or more alternative titles considered together as a specific combination or set.
-
D.
hasAlternativeEditionTitle
Indicates that an entity has a different or variant title used in another edition of the same work.
-
E.
hasAlternativeTitleForPart
Indicates that a specific part or segment of a work is known by an alternative title.
- 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_69f76e2320748190b7f5c4750d0cd0d3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fde5d7d9548190880a9d95b8f0f66b |
completed | May 8, 2026, 1:32 p.m. |
| PD | Predicate disambiguation | batch_69fde4e1bf9c81909754545275eccc03 |
completed | May 8, 2026, 1:28 p.m. |
Created at: May 3, 2026, 4:07 p.m.