Triple
T17346149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | What Is It Like to Be a Bat? |
E421692
|
entity |
| Predicate | exampleFeatureDiscussed |
P80690
|
FINISHED |
| Object | echolocation |
—
|
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: echolocation | Statement: [What Is It Like to Be a Bat?, exampleFeatureDiscussed, echolocation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exampleFeatureDiscussed Context triple: [What Is It Like to Be a Bat?, exampleFeatureDiscussed, echolocation]
-
A.
discoveredFeature
Indicates that an entity has identified or uncovered a previously unknown or unrecognized feature of another entity or object.
-
B.
featuresIn
chosen
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
-
C.
featuresSample
Indicates that an entity includes or presents a particular sample as one of its components or examples.
-
D.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
E.
displaysFeature
Indicates that one entity presents, shows, or makes visible a particular feature or characteristic of another entity.
- 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a2923b48190a5d1abd3f535c59f |
completed | April 19, 2026, 2:12 a.m. |
| PD | Predicate disambiguation | batch_69e3b02662d08190a07d0fb5c04b6f33 |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:44 a.m.