Triple
T4111948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amphibia |
E90196
|
entity |
| Predicate | hasScales |
P54702
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [Amphibia, hasScales, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScales Context triple: [Amphibia, hasScales, false]
-
A.
hasScale
Indicates that one entity possesses or is characterized by a scale or graduated measurement system related to another entity.
-
B.
usesScaleDegrees
Indicates that something is expressed, analyzed, or organized in terms of musical scale degrees rather than absolute pitches.
-
C.
associatedScale
Indicates that one entity is linked or connected to a particular scale used to measure, classify, or evaluate it.
-
D.
hasScaleFactorForm
Indicates that one entity is represented as a scaled version or proportional form of another, typically via a specific scale factor.
-
E.
hasMeasurementMarkings
Indicates that one entity bears visible measurement indicators or scale markings on its surface for quantifying something.
- 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_69aed95c080881908125e30c5dcdc6f8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03d7240c8190a64dcbc669772808 |
completed | March 9, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69af0183eb84819087d7184de28f5514 |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af03d5cce88190ad53bc6cfe10b21e |
completed | March 9, 2026, 5:31 p.m. |
Created at: March 9, 2026, 3:41 p.m.