Triple
T31616880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General James Mattoon Scott |
E806780
|
entity |
| Predicate | fictionalBranch |
P194523
|
FINISHED |
| Object | United States Army |
—
|
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: United States Army | Statement: [General James Mattoon Scott, fictionalBranch, United States Army]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalBranch Context triple: [General James Mattoon Scott, fictionalBranch, United States Army]
-
A.
fictionalOrigin
Indicates that one entity originates from, or was first introduced within, a fictional work, universe, or narrative created by another entity.
-
B.
fictionalSubseries
Indicates that one fictional work or series is a subordinate subseries or installment within a larger fictional series or franchise.
-
C.
fictionalField
Indicates that the subject is associated with a fictional or imaginary field, domain, or area rather than a real-world one.
-
D.
fictionalSon
Indicates that one entity is portrayed as the son of another entity within a fictional or narrative context.
-
E.
fictionalType
Indicates that one entity is a fictional or imaginary type or category of the other entity.
- 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_69f348d61f2081908cad94bc9ffbb671 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fd783fed9c81909e792702636c4f1f |
completed | May 8, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69fd7788e63c81909de22fdafcfe41c0 |
completed | May 8, 2026, 5:41 a.m. |
| PDg | Predicate description generation | batch_69fd783e9e5c819087dec7fefa03700d |
completed | May 8, 2026, 5:44 a.m. |
Created at: April 30, 2026, 10:39 p.m.