Triple
T5884663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buffalo Bill |
E130830
|
entity |
| Predicate | keepsVictimsIn |
P59760
|
FINISHED |
| Object | pit in his basement |
—
|
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: pit in his basement | Statement: [Buffalo Bill, keepsVictimsIn, pit in his basement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: keepsVictimsIn Context triple: [Buffalo Bill, keepsVictimsIn, pit in his basement]
-
A.
hasVictims
chosen
Indicates that an entity has one or more individuals who have been harmed, injured, or adversely affected by it.
-
B.
coVictim
Indicates that two or more entities are victims in the same harmful event or incident.
-
C.
isVictimOf
Indicates that one entity suffers harm, loss, or wrongdoing as a result of another entity’s actions or events.
-
D.
numberOfSuspectedVictims
Indicates the count of individuals believed or alleged to be victims in a particular incident, case, or context.
-
E.
numberOfVictimsKilled
Indicates the count of victims who were killed as a result of the referenced event or action.
- 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_69c0085628dc8190b334c1b44c067efc |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03fe07b7081909f8577ec3a9a1a8d |
completed | March 22, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69c0334bdc308190ad0d7199ab975588 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:57 p.m.