Triple
T36660685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battleship Fuso |
E905113
|
entity |
| Predicate | survivorsCountApproximate |
P176761
|
FINISHED |
| Object | very few |
—
|
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: very few | Statement: [Battleship Fuso, survivorsCountApproximate, very few]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: survivorsCountApproximate Context triple: [Battleship Fuso, survivorsCountApproximate, very few]
-
A.
estimatedNumberOfSurvivors
chosen
Indicates the approximate count of individuals expected to remain alive after a specific event or situation.
-
B.
estimatedNumberOfPeopleSaved
Indicates the approximate count of individuals whose lives were preserved or harm was averted as a result of a particular action, intervention, or entity.
-
C.
survivorCount
Indicates the number of entities that remain alive or intact after a specified event, process, or condition.
-
D.
hasApproximateNumberOfVictims
Indicates that an entity is associated with an estimated, non-exact count of victims.
-
E.
estimatedNumberOfSurvivorsAtLiberation
Indicates the approximate count of individuals who were still alive at the time a camp or similar site was liberated.
- 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_69f76e6e3b908190970251b30f76ad71 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c9f5a8848190ba956ff27f44e396 |
completed | May 3, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:11 p.m.