Triple
T2055298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red-tailed hawk |
E45659
|
entity |
| Predicate | vocalizationUsage |
P35625
|
FINISHED |
| Object | often used in films to represent eagles |
—
|
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: often used in films to represent eagles | Statement: [Red-tailed hawk, vocalizationUsage, often used in films to represent eagles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vocalizationUsage Context triple: [Red-tailed hawk, vocalizationUsage, often used in films to represent eagles]
-
A.
vocalization
Indicates the act or manner of producing sounds or calls, typically as a means of communication.
-
B.
vocalizationMethod
Indicates the manner or technique by which an entity produces a sound or vocal expression.
-
C.
vocalizationCharacteristic
Indicates how an entity’s vocal sounds are characterized, such as their quality, style, or distinctive acoustic features.
-
D.
vocalForces
Indicates a relationship where one entity uses vocal expression (such as speech, singing, or sound) to exert influence, pressure, or compulsion on another entity.
-
E.
usesVoiceAssistant
Indicates that an entity regularly operates or interacts with a voice-controlled digital assistant.
- 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_69a8891a19508190a12ef1e192308dcb |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9a9ce548190a5a3488fafb2e79e |
completed | March 7, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_69abb7abba508190b872f345d3ba51bb |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb94ec400819097596732aabed854 |
completed | March 7, 2026, 5:36 a.m. |
Created at: March 4, 2026, 7:40 p.m.