Triple
T20772632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William F. Garrison |
E511273
|
entity |
| Predicate | serviceNumberOfConflicts |
P10327
|
FINISHED |
| Object | 1+ (including Somalia) |
—
|
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: 1+ (including Somalia) | Statement: [William F. Garrison, serviceNumberOfConflicts, 1+ (including Somalia)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceNumberOfConflicts Context triple: [William F. Garrison, serviceNumberOfConflicts, 1+ (including Somalia)]
-
A.
numberOfConflicts
chosen
Indicates the count of distinct conflicts associated with or involving a given entity or situation.
-
B.
numberOfDisputations
Indicates the quantity of disputations (formal debates or arguments) associated with an entity.
-
C.
hasOngoingConflict
Indicates that there is a current, unresolved state of opposition, dispute, or hostilities between the related entities.
-
D.
servedConflict
Indicates that an entity participated in or rendered service during a specific conflict, war, or military engagement.
-
E.
conflictsOccurIn
Indicates that one or more conflicts take place within, or are situated in, a specified context, location, or setting.
- 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_69e0b4ca01148190ac018e57e0cab46f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2681ff88190bfe5938c2db6b2c4 |
completed | April 21, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69e5c0550ec481908a0877fb2409d983 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:37 p.m.