Triple
T6737431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyudmila Pavlichenko |
E153990
|
entity |
| Predicate | serviceNumberOfConfirmedKills |
P72662
|
FINISHED |
| Object | 309 |
—
|
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: 309 | Statement: [Lyudmila Pavlichenko, serviceNumberOfConfirmedKills, 309]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceNumberOfConfirmedKills Context triple: [Lyudmila Pavlichenko, serviceNumberOfConfirmedKills, 309]
-
A.
killersPerMatch
Indicates the number of kills attributed to an entity in a single match or game instance.
-
B.
serviceNumberOfVictories
Indicates the number of victories achieved in the context of a particular service or service-related activity.
-
C.
numberOfPerpetratorsKilled
Indicates the count of perpetrators who were killed in the context of the described event or incident.
-
D.
numberOfVictimsKilled
Indicates the count of victims who were killed as a result of the referenced event or action.
-
E.
hasVictimCount
Indicates the number of victims associated with a particular event, action, or entity.
- 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_69c6880d84d8819095d19de2295f26ac |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1850a288190aa7e647fefbb0ede |
completed | March 27, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69c6d09067a0819087ed6c820f4699f8 |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d14e18d481908aaac34897c650f1 |
completed | March 27, 2026, 6:49 p.m. |
Created at: March 27, 2026, 2:10 p.m.