Triple
T27420314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Cross |
E693022
|
entity |
| Predicate | victimizedBy |
P50002
|
FINISHED |
| Object | Kitty March |
—
|
NE NERFINISHED |
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: Kitty March | Statement: [Christopher Cross, victimizedBy, Kitty March]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimizedBy Context triple: [Christopher Cross, victimizedBy, Kitty March]
-
A.
isVictimOf
chosen
Indicates that one entity suffers harm, loss, or wrongdoing as a result of another entity’s actions or events.
-
B.
allegedVictimOf
Indicates that one entity is claimed or reported to have been harmed, wronged, or victimized by another entity, without asserting that the claim is proven.
-
C.
portraysAsVictim
Indicates that one entity represents or depicts another entity as a victim in a given context or narrative.
-
D.
threatenedVictim
Indicates that one entity has issued or posed a threat of harm or adverse consequences toward another entity.
-
E.
honorsVictimOf
Indicates that one entity pays tribute or respect to another entity who has suffered harm, loss, or injustice.
- 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_69ef5208617081908f731d312e0fd1bc |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f661b58ac48190907b6c6e9ccc2c59 |
completed | May 2, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69f660eea4648190b0d5e24293607813 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 27, 2026, 12:35 p.m.