Triple
T9815822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Allen |
E238400
|
entity |
| Predicate | hasSpousePoliticalAlignment |
P53206
|
FINISHED |
| Object | abolitionist |
—
|
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: abolitionist | Statement: [Elizabeth Allen, hasSpousePoliticalAlignment, abolitionist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpousePoliticalAlignment Context triple: [Elizabeth Allen, hasSpousePoliticalAlignment, abolitionist]
-
A.
spousePoliticalAlignment
chosen
Indicates that two individuals are spouses and specifies the political alignment or affiliation associated with that spousal relationship.
-
B.
spousePoliticalMovement
Indicates that the political movement is one with which the spouse of the subject is affiliated or identified.
-
C.
spouseMemberOf
Indicates that a person’s spouse is a member of a specified group, organization, or entity.
-
D.
spouseNumberOfTermsInOffice
Indicates the number of distinct terms in office that the spouse of the referenced entity has served.
-
E.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
- 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_69ca84dfde1481909f47c286d715f892 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb2f341648190bf8343e1124085cb |
completed | April 2, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cd03e01ea881909a7d93fc3994ace5 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:30 p.m.