Triple
T29002661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Red-Haired Girl |
E736344
|
entity |
| Predicate | storyDeviceType |
P171012
|
FINISHED |
| Object | offstage character |
—
|
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: offstage character | Statement: [Little Red-Haired Girl, storyDeviceType, offstage character]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyDeviceType Context triple: [Little Red-Haired Girl, storyDeviceType, offstage character]
-
A.
testedDeviceType
Indicates that one entity is the type or category of device on which another entity has been tested.
-
B.
targetedDevice
Indicates that one entity is the specific device toward which another entity’s action, effect, or configuration is directed.
-
C.
controlsDeviceType
Indicates that an entity has authority over or can operate a specific type or category of device.
-
D.
characteristicDevice
Indicates that a device is a defining or typical instrument, tool, or equipment associated with a particular entity, context, or activity.
-
E.
portraysDevice
Indicates that one entity visually represents or depicts a device in some medium or context.
- 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_69f077eb81e88190ad9ff62cbb9f555e |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f6984bb55c8190862eb8796868d188 |
completed | May 3, 2026, 12:35 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f6978ec27c8190a488e1f9c2566d38 |
completed | May 3, 2026, 12:32 a.m. |
Created at: April 28, 2026, 9:35 a.m.