Triple
T26928103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harriet Hemings |
E678136
|
entity |
| Predicate | legalStatusAtDeparture |
P182740
|
FINISHED |
| Object | enslaved person allowed to leave |
—
|
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 person allowed to leave | Statement: [Harriet Hemings, legalStatusAtDeparture, enslaved person allowed to leave]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStatusAtDeparture Context triple: [Harriet Hemings, legalStatusAtDeparture, enslaved person allowed to leave]
-
A.
legalStatusAtArrival
Indicates the legal status or classification an entity held at the time it first arrived at a particular place or jurisdiction.
-
B.
illegalityStatusAtDeparture
Indicates whether an entity’s departure from a location or jurisdiction was illegal at the time it occurred.
-
C.
legalStatusInHomeland
Indicates the legal status or classification an entity holds within its country or place of origin.
-
D.
travelDocumentStatus
Indicates the current state or validity of a person’s travel document in relation to a specific trip or border-crossing process.
-
E.
hasBorderControlStatus
Indicates the type or condition of border control that applies to a given entity or location.
- F. None of above. chosen
Provenance (4 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_69eeeb4cac908190a45956c2993d1cc2 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f7908ec35881909a42f954fb9fa16e |
completed | May 3, 2026, 6:14 p.m. |
| PD | Predicate disambiguation | batch_69f78e2ac3fc819081a45c6841375c8d |
completed | May 3, 2026, 6:04 p.m. |
| PDg | Predicate description generation | batch_69f78fd3fd888190b7db0b563f298585 |
completed | May 3, 2026, 6:11 p.m. |
Created at: April 27, 2026, 6:10 a.m.