Triple
T16891439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 9th Battalion, Royal Australian Regiment |
E424181
|
entity |
| Predicate | casualtiesWounded |
P124874
|
FINISHED |
| Object | 150+ |
—
|
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: 150+ | Statement: [9th Battalion, Royal Australian Regiment, casualtiesWounded, 150+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesWounded Context triple: [9th Battalion, Royal Australian Regiment, casualtiesWounded, 150+]
-
A.
casualtiesCiviliansWounded
Indicates that an event or action resulted in civilian individuals being wounded or injured.
-
B.
casualtiesBritishWounded
Indicates the number of British individuals who were wounded as a result of a specific event or action.
-
C.
casualtiesKilledAndMortallyWounded
Indicates that the relationship records the number of individuals who were killed outright or died later from mortal wounds.
-
D.
wasWoundedIn
Indicates that an entity sustained an injury as a result of a specified event, situation, or conflict.
-
E.
woundedAt
Indicates that an entity was injured or harmed at a specific place or during a particular event.
- F. None of above. chosen
Provenance (4 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3bbc5a5308190937ebd05356bd91d |
completed | April 18, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69e32b90ec3c819099c51bb7baf2984c |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e32e2c07b081908c8fee9f5507bb9e |
completed | April 18, 2026, 7:09 a.m. |
Created at: April 10, 2026, 5:29 a.m.