Triple
T14192099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tai Lung |
E351735
|
entity |
| Predicate | inUniverseCrime |
P11256
|
FINISHED |
| Object | attacked the Valley of Peace |
—
|
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: attacked the Valley of Peace | Statement: [Tai Lung, inUniverseCrime, attacked the Valley of Peace]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inUniverseCrime Context triple: [Tai Lung, inUniverseCrime, attacked the Valley of Peace]
-
A.
crimeRate
Indicates the frequency or level of criminal activity occurring within a given area or population.
-
B.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
C.
regionOfCrimes
Indicates the geographic area or jurisdiction in which the crimes occurred or are attributed to an entity.
-
D.
committedCrime
chosen
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
E.
criminalType
Indicates the specific category or classification of crime associated with a criminal act or offender.
- 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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61e0a52081908213aa6e548d4418 |
completed | April 14, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69de05baed64819096590e5618a3a8ed |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:04 a.m.