Triple
T378785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abigail Adams |
E8629
|
entity |
| Predicate | ordinalPosition |
P2953
|
FINISHED |
| Object | second First Lady of the United States |
—
|
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 First Lady of the United States | Statement: [Abigail Adams, ordinalPosition, second First Lady of the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ordinalPosition Context triple: [Abigail Adams, ordinalPosition, second First Lady of the United States]
-
A.
ordinalNumber
Indicates the position or rank of an entity within an ordered sequence (e.g., first, second, third).
-
B.
ordinalInOffice
chosen
Indicates the numerical order or rank of an individual’s term or tenure in a particular office or position.
-
C.
namePosition
Indicates the positional or ordering relationship of a name within a sequence or structured context (e.g., first, last, or specific index).
-
D.
positionOn
Indicates that one entity is located on top of or at a specific place along the surface or extent of another entity.
-
E.
isPositionOf
Indicates that one entity represents the spatial or organizational position or location of 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec2974988190a1d6316cbb5159c8 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e964d4b481909290e474b0341e3c |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.