Triple
T28143564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neuve-Chapelle |
E714413
|
entity |
| Predicate | hasWarDamageHistory |
P16536
|
FINISHED |
| Object | heavily damaged in World War I |
—
|
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: heavily damaged in World War I | Statement: [Neuve-Chapelle, hasWarDamageHistory, heavily damaged in World War I]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWarDamageHistory Context triple: [Neuve-Chapelle, hasWarDamageHistory, heavily damaged in World War I]
-
A.
sufferedDamageTo
Indicates that one entity has experienced harm, loss, or deterioration affecting another entity or one of its parts.
-
B.
warDamage
chosen
Indicates damage that was caused as a direct consequence of war or armed conflict.
-
C.
hasFireHistory
Indicates that an entity has experienced one or more fire events in the past.
-
D.
hasNotableWar
Indicates that an entity is associated with a significant or historically important war.
-
E.
hasHistoricalPeriodOfConflict
Indicates that there exists a specific historical period during which the related entities were engaged in conflict or hostilities.
- 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_69efd6b033208190bf74f80a147e2092 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f6b49436b0819094e21603054d05d4 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a5fd8481909433e923c5e24e55 |
completed | May 3, 2026, 2:32 a.m. |
Created at: April 27, 2026, 9:55 p.m.