Triple
T23256027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capture of Guam |
E581871
|
entity |
| Predicate | noCombatDeaths |
P151551
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Capture of Guam, noCombatDeaths, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: noCombatDeaths Context triple: [Capture of Guam, noCombatDeaths, true]
-
A.
militaryDeaths
Indicates the number of individuals who died while serving in a military capacity, typically during armed conflict or related operations.
-
B.
nativeCasualties
Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
-
C.
deathToll
Indicates the number of deaths resulting from a particular event, situation, or cause.
-
D.
diedInConflict
Indicates that an entity lost their life as a direct result of a specific conflict or war.
-
E.
conflictOfDeath
Indicates a relationship where a death occurs as a result of, or in the context of, an armed conflict or war.
- 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_69e246079f58819085eaa9c260906880 |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f194c4905c819099ca21c6529413ac |
completed | April 29, 2026, 5:19 a.m. |
| PD | Predicate disambiguation | batch_69effce4d704819092826931d430e8c4 |
completed | April 28, 2026, 12:18 a.m. |
| PDg | Predicate description generation | batch_69f01d8770d081908897c28b04e5faea |
completed | April 28, 2026, 2:37 a.m. |
Created at: April 17, 2026, 4:11 p.m.