Triple
T27005365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aum Shinrikyo |
E680225
|
entity |
| Predicate | notableInjuryCount |
P199972
|
FINISHED |
| Object | over 5,000 injured in Tokyo subway sarin attack |
—
|
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: over 5,000 injured in Tokyo subway sarin attack | Statement: [Aum Shinrikyo, notableInjuryCount, over 5,000 injured in Tokyo subway sarin attack]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableInjuryCount Context triple: [Aum Shinrikyo, notableInjuryCount, over 5,000 injured in Tokyo subway sarin attack]
-
A.
hasInjuries
Indicates that an entity has sustained one or more physical or bodily injuries.
-
B.
injuredIn
Indicates that an entity sustained an injury as a result of a specified event, situation, or action.
-
C.
injuryInvolvedPlayer
Indicates that a specific player is involved in, affected by, or associated with a particular injury event.
-
D.
injuryStatus
Indicates the condition or state of harm, damage, or physical injury affecting an entity.
-
E.
injuryYear
Indicates the year in which an injury occurred or was recorded for the 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_69eeeb53939c8190bd431f32b060f01f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69ff691f5ae481908597ce245188d31c |
completed | May 9, 2026, 5:04 p.m. |
| PD | Predicate disambiguation | batch_69ff67ceeeb081909fd00cad166c4b6a |
completed | May 9, 2026, 4:58 p.m. |
| PDg | Predicate description generation | batch_69ff691e86d0819099fdb5eca5a95632 |
completed | May 9, 2026, 5:04 p.m. |
Created at: April 27, 2026, 7 a.m.