Triple
T37523014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HMS Queen Charlotte (1790) |
E932829
|
entity |
| Predicate | lossOfLifeInFire |
P154199
|
FINISHED |
| Object | heavy casualties |
—
|
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: heavy casualties | Statement: [HMS Queen Charlotte (1790), lossOfLifeInFire, heavy casualties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lossOfLifeInFire Context triple: [HMS Queen Charlotte (1790), lossOfLifeInFire, heavy casualties]
-
A.
destroyedByFire
Indicates that something has been ruined, damaged, or rendered unusable as a direct result of a fire.
-
B.
numberOfDeathsInFireDescription
chosen
Indicates the described count or details of deaths that occurred as a result of a fire.
-
C.
consequenceOfFire
Indicates that something occurs as a result or outcome of a fire.
-
D.
partiallyDestroyedByFire
Indicates that an entity has been damaged to some extent, but not completely destroyed, as a result of a fire.
-
E.
houseBurned
Indicates that a house has been destroyed or significantly damaged by fire.
- 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_69f76ec8862c8190bfa24145f5480642 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba5eec0448190a5e6f0c43fdcd0e3 |
completed | May 6, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69fba34edd548190bfa980e6e16e0a88 |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.