Triple
T25651237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas (enslaved husband) |
E643103
|
entity |
| Predicate | spouseLegalStatus |
P81807
|
FINISHED |
| Object | enslaved |
—
|
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: enslaved | Statement: [Thomas (enslaved husband), spouseLegalStatus, enslaved]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseLegalStatus Context triple: [Thomas (enslaved husband), spouseLegalStatus, enslaved]
-
A.
spouseStatus
Indicates the marital relationship status between two individuals, such as whether they are currently spouses, formerly spouses, or not married to each other.
-
B.
marriageLegalStatus
chosen
Indicates the legal status of a marriage relationship between entities, such as whether it is valid, invalid, pending, or dissolved under applicable law.
-
C.
spouseIllegitimacyStatus
Indicates the legal or social legitimacy status (e.g., legitimate, illegitimate) of a person’s spouse within the context of their relationship.
-
D.
spouseType
Indicates the specific role or category of a person within a spousal relationship (e.g., husband, wife, partner).
-
E.
spouseState
Indicates the marital status or condition of a person’s spouse in relation to them.
- 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_69e77e7d8a848190a98d0162325fd780 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a731508190bb0c8c2462eba224 |
completed | May 2, 2026, 7:33 p.m. |
Created at: April 21, 2026, 6:23 p.m.