Triple
T33252154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ian Campbell |
E851276
|
entity |
| Predicate | hasNotableVictimRoleIn |
P870
|
FINISHED |
| Object | The Onion Field case |
E2039843
|
NE 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: The Onion Field case | Statement: [Ian Campbell, hasNotableVictimRoleIn, The Onion Field case]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableVictimRoleIn Context triple: [Ian Campbell, hasNotableVictimRoleIn, The Onion Field case]
-
A.
hasVictimRoleWith
Indicates a relationship in which one entity occupies or is assigned the role of victim in relation to another entity or event.
-
B.
hasTypicalVictimRole
Indicates that an entity typically occupies the role of a victim in the context of a particular action, event, or relationship.
-
C.
hasVictimSupportRole
Indicates that an entity holds a role or responsibility related to providing support or assistance to a victim.
-
D.
hasMainVictim
Indicates that an event, action, or harmful situation primarily targets or affects a specific victim as its main subject.
-
E.
notableVictim
chosen
Indicates that the subject is a person or entity who is notably recognized as a victim of the object (such as an event, crime, or harmful action).
- F. None of above.
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_69f34963135c819084e7f1d483421f00 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a019b8995dc819088727aa023beadce |
completed | May 11, 2026, 9:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3539121f208190952b0790b6e47606 |
completed | June 19, 2026, 12:41 p.m. |
| PD | Predicate disambiguation | batch_6a01961bb748819096a941f1b5443908 |
completed | May 11, 2026, 8:40 a.m. |
Created at: May 1, 2026, 1:31 a.m.