Triple
T38693898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henderson lorikeet |
E949941
|
entity |
| Predicate | hasTongueType |
P195432
|
FINISHED |
| Object | brush-tipped tongue |
—
|
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: brush-tipped tongue | Statement: [Henderson lorikeet, hasTongueType, brush-tipped tongue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTongueType Context triple: [Henderson lorikeet, hasTongueType, brush-tipped tongue]
-
A.
hasTypeOfMouth
Indicates that an entity possesses a mouth characterized by a specific type or form.
-
B.
tongueLength
Indicates the length of an entity’s tongue, typically as a measurable physical attribute.
-
C.
tongued
Indicates that one entity touches, licks, or stimulates another entity using its tongue.
-
D.
tongueFunction
Indicates how a tongue is used or operates in performing its roles or actions.
-
E.
tonguedIn
Indicates that one entity is inserting or has inserted their tongue into another entity, typically in a sexual or intimate 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_69f76f0124408190bb39c3040734846b |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fdd07a34c08190982b8c61c2775cf6 |
completed | May 8, 2026, noon |
| PD | Predicate disambiguation | batch_69fdbd25c7908190b72fca8de7ce503f |
completed | May 8, 2026, 10:38 a.m. |
| PDg | Predicate description generation | batch_69fdd07724f88190a33ec602642d2ea3 |
completed | May 8, 2026, noon |
Created at: May 3, 2026, 4:33 p.m.