Triple
T212070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sirhan Sirhan |
E4741
|
entity |
| Predicate | allegedMotive |
P6699
|
FINISHED |
| Object | opposition to Robert F. Kennedy’s support for Israel |
—
|
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: opposition to Robert F. Kennedy’s support for Israel | Statement: [Sirhan Sirhan, allegedMotive, opposition to Robert F. Kennedy’s support for Israel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allegedMotive Context triple: [Sirhan Sirhan, allegedMotive, opposition to Robert F. Kennedy’s support for Israel]
-
A.
motive
chosen
Indicates the underlying reason, intention, or driving force that explains why an entity performs or is associated with a particular action or event.
-
B.
accusationType
Indicates the specific category or nature of an accusation made by one party against another.
-
C.
causeOf
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
D.
perpetratedBy
Indicates that an action, event, or wrongdoing was carried out or caused by a particular agent or entity.
-
E.
firstAccused
Indicates that the subject is the primary or earliest individual formally charged or blamed in a particular case or incident.
- 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25d35aa288190966b6e15af1525cb |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b4f71b88190866c8262922ae204 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.