Triple
T3914260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lost Jungle |
E88796
|
entity |
| Predicate | runtimeCharacteristic |
P52542
|
FINISHED |
| Object | multi-chapter serial |
—
|
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: multi-chapter serial | Statement: [The Lost Jungle, runtimeCharacteristic, multi-chapter serial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runtimeCharacteristic Context triple: [The Lost Jungle, runtimeCharacteristic, multi-chapter serial]
-
A.
trainingCharacteristic
Indicates that an entity has a specific property, feature, or quality related to training (such as method, intensity, or style).
-
B.
typicalRuntimeRange
Indicates the usual lower and upper bounds of time typically required for an entity to run or complete its operation.
-
C.
systemCharacteristics
Indicates the defining properties, behaviors, and constraints that characterize how a system operates or is configured.
-
D.
bootTimeCharacteristic
Indicates the duration or properties of the time it takes a system or device to start up from an inactive state.
-
E.
equipmentCharacteristic
Indicates that a specific characteristic, property, or attribute is associated with a piece of equipment.
- F. None of above. chosen
Provenance (4 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_69aed955229881909e85e73ffab1d343 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee75eedcc81908088ff4dbb8be56b |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef18748648190b85e62f7796ff4b4 |
completed | March 9, 2026, 4:12 p.m. |
Created at: March 9, 2026, 3:22 p.m.