Triple
T6232667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Pelée |
E139392
|
entity |
| Predicate | hasSurvivorsCount1902 |
P63871
|
FINISHED |
| Object | very few survivors |
—
|
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 survivors | Statement: [Mount Pelée, hasSurvivorsCount1902, very few survivors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurvivorsCount1902 Context triple: [Mount Pelée, hasSurvivorsCount1902, very few survivors]
-
A.
hasSurvivors
Indicates that one or more entities continue to exist or remain alive after a particular event, condition, or incident.
-
B.
estimatedNumberOfSurvivorsAtLiberation
Indicates the approximate count of individuals who were still alive at the time a camp or similar site was liberated.
-
C.
survivorCount
chosen
Indicates the number of entities that remain alive or intact after a specified event, process, or condition.
-
D.
hasSurvivorTerm
Indicates that an entity is associated with a term or label specifically used to describe survivors of an event, condition, or circumstance.
-
E.
survivingAircraftCount
Indicates the number of aircraft that remain operational or intact after a specified event, condition, or time period.
- 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_69c008b0e7ac8190808a59573ee646f3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062ee6f088190bf72692eb8ffb761 |
completed | March 22, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69c05601de6481909d0880048fd7b49a |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:22 p.m.