Triple
T10498737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ceratiidae |
E247610
|
entity |
| Predicate | femaleMorphology |
P78623
|
FINISHED |
| Object | large mouth with long teeth |
—
|
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: large mouth with long teeth | Statement: [Ceratiidae, femaleMorphology, large mouth with long teeth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: femaleMorphology Context triple: [Ceratiidae, femaleMorphology, large mouth with long teeth]
-
A.
reproductiveSystem
Indicates a relationship where one entity is the reproductive system of another, responsible for producing offspring or reproductive cells.
-
B.
femaleFeature
chosen
Indicates that the subject possesses a characteristic or attribute that is typically associated with females.
-
C.
femaleHas
Indicates that a specified entity is female or possesses a female gender attribute in relation to another entity or context.
-
D.
femaleMass
Indicates that the subject has a mass value specifically associated with its female form or female population.
-
E.
femaleCommonName
Indicates that the associated name is commonly used as a given name for females.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5098e45ec8190a02b981a06786909 |
completed | April 7, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69d4fb8e24ac8190912c9f11b8bd3084 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:25 p.m.