Triple
T17065139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koba |
E414064
|
entity |
| Predicate | scarCause |
P694
|
FINISHED |
| Object | human experimentation and abuse |
—
|
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: human experimentation and abuse | Statement: [Koba, scarCause, human experimentation and abuse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scarCause Context triple: [Koba, scarCause, human experimentation and abuse]
-
A.
causeOf
chosen
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
B.
scarLocation
Indicates the anatomical location on an entity where a scar is present.
-
C.
causeStatus
Indicates that one entity brings about, initiates, or is responsible for a particular state or condition in another entity.
-
D.
eligibleCause
Indicates that one entity qualifies as a valid or acceptable cause or reason for another entity or outcome.
-
E.
mourningCause
Indicates that one entity is in a state of mourning specifically because of the other entity, which is the cause or reason for the grief.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3db806de48190a9ce68b40fc77a74 |
completed | April 18, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69e35d642f74819098c014135e249b27 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:34 a.m.