Triple
T34417289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Manoel |
E883431
|
entity |
| Predicate | sustainedDamageDuring |
P72864
|
FINISHED |
| Object | World War II |
—
|
NE NERFINISHED |
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: World War II | Statement: [Fort Manoel, sustainedDamageDuring, World War II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sustainedDamageDuring Context triple: [Fort Manoel, sustainedDamageDuring, World War II]
-
A.
sufferedDamageTo
chosen
Indicates that one entity has experienced harm, loss, or deterioration affecting another entity or one of its parts.
-
B.
damageTo
Indicates a relationship where one entity causes harm, loss, or deterioration to another entity.
-
C.
tookHeavyDamageAt
Indicates that an entity experienced severe or substantial damage at a specific location or point in time.
-
D.
damageOccurred
Indicates that some form of harm, loss, or deterioration has taken place as a result of an event or action.
-
E.
damageLeadsTo
Indicates that one instance of damage causally results in or contributes to another specified outcome or condition.
- 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_69f349c2e3b88190a67834eb5bcffeaf |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71947ad88819082ab9d85dd493b01 |
completed | May 3, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69f71824431081908d9685d2462ea242 |
completed | May 3, 2026, 9:40 a.m. |
Created at: May 1, 2026, 1:59 a.m.