Triple
T7809567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Welcome Danger |
E180642
|
entity |
| Predicate | hasSilentVersion |
P79138
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Welcome Danger, hasSilentVersion, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSilentVersion Context triple: [Welcome Danger, hasSilentVersion, yes]
-
A.
hasVersionIn
Indicates that one entity exists as a specific version or variant within the context, format, or system represented by another entity.
-
B.
hasSpecialVersion
Indicates that an entity possesses or is associated with a distinct or customized version of another entity, differing from the standard or default form.
-
C.
hasVersionNumber
Indicates that an entity is associated with a specific version identifier or number.
-
D.
hasStandardVersion
Indicates that one entity serves as the official or canonical version of another entity.
-
E.
hasEarlierVersion
Indicates that one entity is an earlier or prior version of another entity in a version sequence.
- 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_69ca827f6f148190beca4e245b993506 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78bb4b08190b2b3b51c5a0a033c |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae91687788190af9cb7aaa996d291 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7855a3c81908b9318f7186fc0c0 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:37 p.m.