Triple
T22447095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parcel |
E554888
|
entity |
| Predicate | supportsLanguage |
P2177
|
FINISHED |
| Object | Sass |
—
|
NE NERFINISHED |
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: Sass | Statement: [Parcel, supportsLanguage, Sass]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sass Context triple: [Parcel, supportsLanguage, Sass]
-
A.
Sass
chosen
Sass is a popular CSS preprocessor language that extends standard CSS with features like variables, nesting, mixins, and functions to enable more powerful and maintainable styling.
-
B.
Stylus CSS preprocessor
Stylus is a dynamic CSS preprocessor that adds powerful features like variables, mixins, and flexible syntax to streamline and enhance stylesheet authoring for web development.
-
C.
CSS
CSS is a professional society within the IEEE focused on the theory, design, and application of control systems in engineering and related fields.
-
D.
CSS
CSS is a U.S. cryptologic organization that partners with the National Security Agency to coordinate signals intelligence and information assurance activities across the armed forces.
-
E.
CSS
CSS is Pakistan’s highly competitive federal civil service examination system used to recruit officers for various government ministries and departments.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b48be0481909f4601b732424e5b |
completed | April 29, 2026, 1:13 a.m. |
Created at: April 16, 2026, 8:47 p.m.