Triple
T36938737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorraine Blake |
E913688
|
entity |
| Predicate | spouseUnit |
P94788
|
FINISHED |
| Object | 4077th Mobile Army Surgical Hospital |
—
|
NE NERFINISHED |
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: 4077th Mobile Army Surgical Hospital | Statement: [Lorraine Blake, spouseUnit, 4077th Mobile Army Surgical Hospital]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseUnit Context triple: [Lorraine Blake, spouseUnit, 4077th Mobile Army Surgical Hospital]
-
A.
spouseOfMilitaryUnit
chosen
Indicates that one entity is the spouse or marital partner of a member associated with the specified military unit.
-
B.
spouseMember
Indicates that one entity is the spouse (married partner) of another entity.
-
C.
spouseInFamily
Indicates that a person is a spouse (married partner) within the context of a specific family unit.
-
D.
spouse
Indicates that two entities are married to each other in a legally or socially recognized partnership.
-
E.
spouseIn
Indicates that one entity is the spouse (married partner) of another entity within a specified context or grouping.
- 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_69f76e8a6a5c81909c1febf32bf3fe23 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe91383a1c81909266e40c3c3ede6c |
completed | May 9, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69fe8fde094081908f0f121664fbb5c7 |
completed | May 9, 2026, 1:37 a.m. |
Created at: May 3, 2026, 4:13 p.m.