Triple
T32708308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jakarta Server Faces |
E836331
|
entity |
| Predicate | viewDefinitionLanguage |
P174820
|
FINISHED |
| Object | Facelets |
—
|
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: Facelets | Statement: [Jakarta Server Faces, viewDefinitionLanguage, Facelets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewDefinitionLanguage Context triple: [Jakarta Server Faces, viewDefinitionLanguage, Facelets]
-
A.
languageView
Indicates a relationship where one entity views, interprets, or presents another entity through the lens of a particular language or linguistic perspective.
-
B.
dataModelLanguage
Indicates that one entity is a language or formalism used to define, describe, or structure the data model of another entity.
-
C.
viewOnGodLanguage
Indicates a relationship where an entity’s perspective, stance, or interpretation regarding language used about God is specified.
-
D.
languageDisplays
Indicates that one entity presents, shows, or renders another entity in a particular language or linguistic form.
-
E.
languageOfInterface
Indicates the language used by or presented in a user interface.
- 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_69f3493446148190819541f3ffe79975 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c87bf9c481908804bd231d60cd30 |
completed | May 3, 2026, 4:01 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f617c08190a70ba880210f908c |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c77500a08190b2bdeca33bd2ac08 |
completed | May 3, 2026, 3:56 a.m. |
Created at: May 1, 2026, 1:10 a.m.