Triple
T28609359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | StackGuard |
E724133
|
entity |
| Predicate | targetsLanguage |
P183492
|
FINISHED |
| Object | C |
—
|
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: C | Statement: [StackGuard, targetsLanguage, C]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetsLanguage Context triple: [StackGuard, targetsLanguage, C]
-
A.
targetLanguage
Indicates the language that is the intended recipient or focus of a communication, translation, or linguistic operation.
-
B.
languageTargets
Indicates that a language is specifically directed at, intended for, or used to address a particular target entity (such as an audience, system, or domain).
-
C.
linguisticTarget
Indicates that something serves as the specific linguistic element (such as a word, phrase, or expression) that is the focus or target of a given action, analysis, or relation.
-
D.
translationTargetLanguage
Indicates the language into which content is being or has been translated.
-
E.
hasTargetAudienceLanguage
Indicates that something is intended for or directed toward an audience that speaks a particular language.
- 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_69f01d816d7c8190a1fe27e3434041dc |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f7a01efcc08190bba489a9099b8684 |
completed | May 3, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
| PDg | Predicate description generation | batch_69f79f477c4c8190a35cb6d87b1dcbd1 |
completed | May 3, 2026, 7:17 p.m. |
Created at: April 28, 2026, 4:29 a.m.